{"as_of":"2026-08-16T14:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:02807b625e063b755b2661310fd62e9a477e3ea4d6154e463c4ddf46b7c81986","coverage":[{"denominator":79,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":79,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:37:22.666794Z","state":"measured"},{"denominator":80,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":80,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:37:22.626754Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T12:37:22.706911Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"cited_work":{"arxiv_id":"1908.06925","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.06925","snapshot_observed_at":"2026-08-14T12:37:22.706911Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","venue":"eess.IV","work_id":"6bcb5918-c294-439c-8cb2-b4159e061581","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.626754Z"},"links":{"cited_paper":"/paper/1908.06925","citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:441bb497c27b8513b16bed2f96a9dad9e793a6bbaf13d9b7e56a649ab7d7e799","observation_id":"d9454fa9-6714-47a0-a34e-8cb6a858c638","resolution":{"observed_at":"2026-08-14T12:37:22.713895Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.06925/citation-record","integrity":"/paper/1908.06925/integrity","json":"/paper/1908.06925/citation-record.json","paper":"/paper/1908.06925"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.296325Z","title":"Hyperspectral remote sensing data analysis and future challenges,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.296325Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:4cc2cb0c91d2fd4d46c3707569e846951f1668de2cf6046c2368472f1bc356bb","observation_id":"7fd466cb-b54f-4841-85dc-7f4ae456b899","resolution":{"observed_at":"2026-08-14T12:37:22.296325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.967098Z","title":"Nonlinear unmixing of hyperspectral images: Models and algorithms,","venue":null,"work_id":"c027e7b2-fd60-4e1f-9628-c316e0cb7e6f","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.302160Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:178644ee4660ad10500493e528d681fc6fb7706f28f592bd11ffa4130a21e3da","observation_id":"eaf58cb8-8911-4e35-b9f3-75c0806af737","resolution":{"observed_at":"2026-08-14T12:37:23.971756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.952306Z","title":"Nonparametric detection of nonlinearly mixed pixels and endmember estimation in hyperspectral images,","venue":null,"work_id":"840b5aae-f03c-43fd-b75c-fe7a9d5388f3","year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.307148Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:b79fee76a795ea83714db1db56acca0185349f66be9b31b1db360ac67f09f7e6","observation_id":"e8d5721a-0545-44e3-92a3-6a41b5c6e2b5","resolution":{"observed_at":"2026-08-14T12:37:23.957358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.938159Z","title":"Endmember variability in spectral mixture analysis: A review,","venue":null,"work_id":"32c157be-03f0-4905-aefc-f646c67d3478","year":2011},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.312264Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:583db8acfc75546b4f4b4a6a95b200807bea807d5e33a2f1aec15d9187cca450","observation_id":"95a6f21e-db92-4a73-a41f-bb80d4daa5ce","resolution":{"observed_at":"2026-08-14T12:37:23.942538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.923629Z","title":"Generalized linear mixing model accounting for endmember variability,","venue":null,"work_id":"e614f8d7-2f01-429e-b832-fa2076093b93","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.317074Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:e8e1775863ba23b9321f2b141d2c57e2f1f8254b78693b9eae9736aaaaa8bfad","observation_id":"8883c18c-433e-4af3-9a76-9f60d3195183","resolution":{"observed_at":"2026-08-14T12:37:23.928794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.908972Z","title":"Super-resolution for hyperspectral and multispectral image fusion accounting for seasonal spectral variability,","venue":null,"work_id":"fe0e453b-a759-4763-8218-6a5618a440bc","year":2020},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.321902Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:81f7f35402198d513e33b08015fe0f9b75318c660f438d69a13a85ba332d3834","observation_id":"0309ce76-d84b-4004-96bf-bffb59870eab","resolution":{"observed_at":"2026-08-14T12:37:23.913702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.895007Z","title":"Deep generative endmember modeling: An application to un- supervised spectral unmixing,","venue":null,"work_id":"3056afca-f1dc-4495-b8ae-cc098ccb41f8","year":2020},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.326957Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:15b50e1b49430157ec2013728cea2d46479ee671a238e3530bddb63d8613326f","observation_id":"c725ef3d-6dfe-4b72-88cb-049f3fe0b1ff","resolution":{"observed_at":"2026-08-14T12:37:23.899271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.881217Z","title":"Deep generative models for library augmentation in multiple endmember spectral mixture analysis,","venue":null,"work_id":"709ca743-571e-4cf2-b337-0ce302c6c88d","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.331556Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:dbcb708d69201da5a7afc3763fea6d5e082d94bd6b9ce2e0a7627d6bfff182bb","observation_id":"8110685d-4118-477d-b658-512b734295cc","resolution":{"observed_at":"2026-08-14T12:37:23.885929Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.867531Z","title":"Nonlinear spectral mixing in desert vegetation,","venue":null,"work_id":"c7e091d1-6767-4411-8329-9118ab1691d4","year":1996},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.340660Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:668f43e6282f4fe897e627c3bf77407138e4579d5c3803a3dd69565e36cb7e7f","observation_id":"c666291b-7ceb-4da0-9e3c-9e7fd1483f34","resolution":{"observed_at":"2026-08-14T12:37:23.872022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.853524Z","title":"A review of nonlinear hyperspec- tral unmixing methods,","venue":null,"work_id":"f34475c4-1404-4a6a-a96b-c45da0ef52d9","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.345282Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:66a89439913a9f301c0d7e6f72b88ab911e090f7a19838787a1960bb15800d73","observation_id":"c66c5536-1e66-49a9-ae4d-56cc1fcf22eb","resolution":{"observed_at":"2026-08-14T12:37:23.858167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.838807Z","title":"Photometric phase functions of common geologic minerals and applications to quantitative analysis of mineral mixture reﬂectance spectra,","venue":null,"work_id":"3304829d-6a10-44ac-8e9f-03167f9ce166","year":1989},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.350245Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:1fd1db1783323fdedffe0cab4c6c1d3558aba6ced3cbe4756b1a9b78a0fdaa7a","observation_id":"a12a7fe4-3595-4835-92a9-c925f3fd01ed","resolution":{"observed_at":"2026-08-14T12:37:23.843604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.824696Z","title":"A quantitative and comparative analysis of linear and nonlinear spectral mixture models using radial basis function neural networks,","venue":null,"work_id":"7724bbba-e5e1-46c0-9e88-0e5fbd7b2ebe","year":2001},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.355084Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:3ed1ebbafb9bc9560c072bed37661229589944f94ac9b8b03c1674543df414e7","observation_id":"c0af91f6-3c15-4558-b1b0-7dfc35f89873","resolution":{"observed_at":"2026-08-14T12:37:23.829613Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.810949Z","title":"Supervised nonlinear spectral unmixing using a postnonlinear mixing model for hy- perspectral imagery,","venue":null,"work_id":"6ccecfcd-ee4d-4895-9031-c039ae33820f","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.359766Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:495a3313c29624940a332b10e61505ebceed4d8e7a62f6af48afc88d9ea9bc1b","observation_id":"10d5cbec-0c4b-4a07-b2e9-b4ac472b9ca7","resolution":{"observed_at":"2026-08-14T12:37:23.815616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.796531Z","title":"Abundance estimation from hyperspec- tral image based on probabilistic outputs of multi-class support vector machines,","venue":null,"work_id":"cddc82cb-0cbd-41d7-bc76-99133d00ac6d","year":2005},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.364174Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:59f54911736285dfb6b723f52c4ada3552a0fdd8f9b80fa50f6c548402d55135","observation_id":"dcd6b4e0-0d07-46db-a1ce-ae4f054fc1c2","resolution":{"observed_at":"2026-08-14T12:37:23.801331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.782167Z","title":"Non-linear spectral unmixing by geodesic simplex volume maximization,","venue":null,"work_id":"39ac39b2-6f43-42e4-b3e1-a95ee58697ab","year":2011},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.368791Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:66c12713bb53d3d7958a2041a7b23b013010aee43b0665fcf60eca7a3e81b5ba","observation_id":"77acbffc-afed-4a97-8cd5-c98605066e1d","resolution":{"observed_at":"2026-08-14T12:37:23.787102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.767408Z","title":"A distance geometric framework for nonlinear hyperspectral unmixing,","venue":null,"work_id":"03ad3a1d-02e4-43e4-b3ac-8cef5f03ce94","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.373407Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:df4e8a806ab00b992950022f42fb51adbdaf0a7ae306c39a195b1bd817eeb000","observation_id":"e7fbd4ee-0bd6-4624-9404-d2800ffd7276","resolution":{"observed_at":"2026-08-14T12:37:23.772370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.752692Z","title":"A kernel spatial complexity-based nonlinear unmixing method of hyperspectral imagery,","venue":null,"work_id":"e24a2064-80d6-40eb-8f9c-82bef832311a","year":2010},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.377962Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:f3edafe2f238649a68f506eaa474f2d3a4edc06610147aa03034c4c24ac01f0f","observation_id":"2ed1cbd0-d4ee-4a26-9c3b-9529d20306c4","resolution":{"observed_at":"2026-08-14T12:37:23.757781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.737873Z","title":"Blind nonlinear hyperspectral unmixing based on constrained kernel nonnegative matrix factorization,","venue":null,"work_id":"7f0278df-8faa-4dec-8717-620fb8247a1e","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.382664Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:82839adb92611ecfcfeb82da1c96e7e11228e37e510cc5c050892334d84da11f","observation_id":"334822d2-9219-48fa-91e6-e09e8162fb0f","resolution":{"observed_at":"2026-08-14T12:37:23.742804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.722506Z","title":"Nonlinear unmixing of hyperspec- tral data based on a linear-mixture/nonlinear-ﬂuctuation model,","venue":null,"work_id":"6b4706d7-1fa5-442e-b93c-65218e1fbb42","year":2013},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.387255Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:98c0bbdd1ed0f039e209913ff518c5e23843644e4e18e00c48f8138f2c5aff5f","observation_id":"97d7a2ab-7d13-4554-9c9c-802e1cb02285","resolution":{"observed_at":"2026-08-14T12:37:23.727544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.708019Z","title":"Nonlinear estimation of material abundances in hyperspectral images with 𝓁1-norm spatial regularization,","venue":null,"work_id":"73bd4ab2-c971-4968-b5e2-4a83dcca55ef","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.391843Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:5329cafdb82fd8e43878193f9fcada1d3a7e9f2b0ce97cd3b2a2d7bc75f42c6d","observation_id":"687e25b4-d780-49df-a488-791660455946","resolution":{"observed_at":"2026-08-14T12:37:23.712529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.691879Z","title":"Nonlin- ear spectral unmixing of hyperspectral images using gaussian processes,","venue":null,"work_id":"edd23a27-7147-45d6-852c-1d806948dabd","year":2013},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.396440Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:5098b21118dbe8cd426f0c9699c978ddf89644a8dd0896989e9c0c69fd57e189","observation_id":"de821871-9ba7-4a27-8298-a1681bf0e222","resolution":{"observed_at":"2026-08-14T12:37:23.697194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.676007Z","title":"Nonlinear unmixing of hyperspectral data with vector-valued kernel functions,","venue":null,"work_id":"4a86b0cd-a231-4bab-9bdd-1155b9c98ec5","year":2017},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.401161Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:6d03859f28171be73d97fbd4bfda19490b9854ee981b2c838836b8cfc6a130fe","observation_id":"45c17a8c-7dfc-4fc0-8c8f-55ab5f2b10be","resolution":{"observed_at":"2026-08-14T12:37:23.680696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.660906Z","title":"Incorporating spatial information in spectral unmixing: A review,","venue":null,"work_id":"3935725e-475e-4b6d-8b9e-1649699d459a","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.405723Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:2c1a28f8e42af2df6a81c8632636be737aefeb41202cfc61d64b2895c497d142","observation_id":"ae8ab53c-ad87-4995-be22-b482835f5e79","resolution":{"observed_at":"2026-08-14T12:37:23.665626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.646313Z","title":"A low-rank tensor regularization strategy for hyperspectral unmixing,","venue":null,"work_id":"35405c84-c16b-4fae-9874-7facbcda43b0","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.409920Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:28559a70777539f29f645aac07da858f78e04d89ec8fa93c25ccfc44dea0a97a","observation_id":"37504439-33d5-4692-9539-41f68235ea3e","resolution":{"observed_at":"2026-08-14T12:37:23.651083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.630537Z","title":"Total variation spatial regularization for sparse hyperspectral unmixing,","venue":null,"work_id":"32c1c867-6b88-48e5-b898-cfcc1e7411ee","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.413928Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:dbaa3605ec81d5f341163d435b6e673814a88254e050289e524473f1159b2391","observation_id":"57aa29df-05c7-499d-9ba7-e709c2ba0d71","resolution":{"observed_at":"2026-08-14T12:37:23.635266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.615369Z","title":"Adaptive spatial regularization sparse unmixing strategy based on joint MAP for hyperspectral remote sensing imagery,","venue":null,"work_id":"32cb74e4-ddfa-4886-a748-e06348084425","year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.417945Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:4a4ec2d2237ab746a64f7414708e27784a5e4a79c1597ae1589f528fd183d57f","observation_id":"b1943470-4983-4c97-90e1-98183edf2ebf","resolution":{"observed_at":"2026-08-14T12:37:23.620492Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.422080Z","title":"Blind hyperspectral unmixing using an extended linear mixing model to address spectral variability,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.422080Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:ad5c82db9c3cf5312b00cf00efe25d04d29171afd3ccccd0e76ba8e27251e436","observation_id":"126ef9af-1cfe-4c1b-bbd9-10af1daf6103","resolution":{"observed_at":"2026-08-14T12:37:22.422080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.589521Z","title":"Low-rank tensor modeling for hyperspectral unmixing accounting for spectral variability,","venue":null,"work_id":"a2f73500-b20f-4b7c-a790-302e3c0480cc","year":2020},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.426447Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:001ae1f5c0ee73f9fa471db89eec79ebb97c8b6b26e41a5e745d1eef0ddc7621","observation_id":"c4e66cde-2b07-4e5e-8855-8f9e268a8e32","resolution":{"observed_at":"2026-08-14T12:37:23.594906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.574036Z","title":"Improved hyperspectral unmixing with endmember variability parametrized using an interpolated scaling tensor,","venue":null,"work_id":"443401a2-377e-4bca-b03a-eff79b104d0f","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.430471Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:770a465212eb965fbfb6a20ce7411525bd712c89661ac79a09e8f4a6ffef95e7","observation_id":"10c5c49b-c4a3-48c5-b761-c0905e535769","resolution":{"observed_at":"2026-08-14T12:37:23.578965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.434998Z","title":"An augmented linear mixing model to address spectral variability for hyperspectral unmixing,","venue":null,"work_id":null,"year":1923},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.434998Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:b84611a6d75af933ec87ef258dd4678b8cd87bdd650a7dd6d4de17df14f0efa5","observation_id":"a2673d55-55c5-4c47-b946-19b5afb119b5","resolution":{"observed_at":"2026-08-14T12:37:22.434998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.550457Z","title":"Sulora: Subspace unmixing with low-rank attribute embedding for hyperspectral data analysis,","venue":null,"work_id":"cf2884df-96ec-454b-b627-46eb2a114a63","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.439707Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:fe11cad1a9db079b98e1bbe716007b7fe8d8d4f459cfeac1a494487dc324b628","observation_id":"ce33873b-ec3c-4374-b4c6-aa64a023ef18","resolution":{"observed_at":"2026-08-14T12:37:23.554601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.537017Z","title":"Relationships between nonlinear and space-variant linear models in hyperspectral image unmixing,","venue":null,"work_id":"9bd91be5-fbb7-4937-8021-947294828d9e","year":2017},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.444421Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:c8c7dcad271633c061177217608de48904f2e537da6c7670c987c4b19f40283c","observation_id":"6d6bc73a-3348-4aaf-9e51-21b61af4c6cc","resolution":{"observed_at":"2026-08-14T12:37:23.541691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.522849Z","title":"Integrating spatial information in the normalized p-linear algorithm for nonlinear hyperspectral unmixing,","venue":null,"work_id":"c066d43d-5cd8-41f0-9e74-4e44dddeaec1","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.449003Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:f980cd00b7403b77aa4cc9208fad30391fdcdadf5f6fbf1ff8d42dc85b4ba8b3","observation_id":"30116281-04c1-4107-b464-d51e265aa0f5","resolution":{"observed_at":"2026-08-14T12:37:23.527681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.508694Z","title":"Nonlinear estimation of material abundances in hyperspectral images with L1-norm spatial regulariza- tion,","venue":null,"work_id":"65b4ce96-513f-4ae1-a23c-f7e15c0e5827","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.453711Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:0e43f8701c69718e37b79525ad36b4d4b2934105143b072dc0c8bce2fb902225","observation_id":"c2091bf0-b463-4c4e-a622-bcf2e8ab317f","resolution":{"observed_at":"2026-08-14T12:37:23.513425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.494604Z","title":"Centralized collaborative sparse unmixing for hyperspectral images,","venue":null,"work_id":"6483652c-df0d-4921-95a7-1eee24f5fe3f","year":1949},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.458703Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:fa09035d22b27fed3928721d8adb53fbaccabd35f8bb513a7dee281d347b2cab","observation_id":"15eba170-1db0-491c-936c-caf240f37c83","resolution":{"observed_at":"2026-08-14T12:37:23.499097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.480102Z","title":"Nonconvex-sparsity and nonlocal-smoothness-based blind hyperspectral unmixing,","venue":null,"work_id":"eca9d581-e8a3-4d30-868c-98c333726ad3","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.463330Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:c42043d437ec51aa4f2804601a603bbc3e3620f5f1f98cd399870e9cf8ea2837","observation_id":"fd102480-61d9-441d-b695-7fd8292fe0a1","resolution":{"observed_at":"2026-08-14T12:37:23.484616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.465743Z","title":"Manifold regularized sparse NMF for hyperspectral unmixing,","venue":null,"work_id":"fde2aff5-23a4-4a65-8c4d-1cf1d4f7b2b7","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.468332Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:dcc53199eeaf74b23377651d43a4e104b48f91a737ca2b770382294017640c04","observation_id":"4da485d9-8342-4b97-b29b-cd264ad6e96f","resolution":{"observed_at":"2026-08-14T12:37:23.470469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.451470Z","title":"A graph laplacian regular- ization for hyperspectral data unmixing,","venue":null,"work_id":"8e5003e8-1c3b-4c05-9336-27bd4a8775d4","year":2015},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.472866Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:8865e8c635daf5da74e951fa742d966d801a878e8dc5e210bceeac37fbf2dfc5","observation_id":"b59a8732-e6bc-4284-bf7c-9265cf35d688","resolution":{"observed_at":"2026-08-14T12:37:23.456269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.438144Z","title":"A fast multiscale spatial regularization for sparse hyperspectral unmixing,","venue":null,"work_id":"27233d19-a807-4bc0-af44-a70a4489ffe3","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.477451Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:6e2ed47d45c713ac5af26e1fcec1af31dc3a11c890c1f280474a426211bef6f6","observation_id":"be5866ea-0d81-4546-b3d8-14f95123793e","resolution":{"observed_at":"2026-08-14T12:37:23.442320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.424818Z","title":"A data dependent multiscale model for hyperspectral unmixing with spectral variability,","venue":null,"work_id":"fefa8b94-ca4a-4318-9926-d4f8dc2b8460","year":2020},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.482011Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:b3bb7ab95e077a9dbb452d5d2c38237c56995be48d6f337a8a59438ff9cdd18a","observation_id":"75576035-674d-4629-805d-5a9b52071bbd","resolution":{"observed_at":"2026-08-14T12:37:23.428804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.409693Z","title":"Regularization pa- rameter estimation for non-negative hyperspectral image deconvolution,","venue":null,"work_id":"4185e141-d114-4538-b232-64f57fce19d6","year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.486727Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:af726f373d778879ae77bfb30847977da2b2e046e29de77ed8f0000dec972a3c","observation_id":"9f58d9a2-cbb7-4cf2-ad48-4a5868234c00","resolution":{"observed_at":"2026-08-14T12:37:23.414953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.395067Z","title":"Functions of positive and negative type and their connection with the theory of integral equations,","venue":null,"work_id":"aae77847-2c5e-4f67-8da5-fac61396bd1b","year":1909},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.491320Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:909f0d4dbf4caae0fc37355887e8dc10e6678c524cb858ccbc1c4b4aca004d07","observation_id":"a871c90d-bcb3-43c9-a9f8-d01848bdb297","resolution":{"observed_at":"2026-08-14T12:37:23.399850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.379251Z","title":"On properly positive hermitian matrices,","venue":null,"work_id":"aad93890-a21d-4598-a841-e06b0d8704c7","year":1916},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.496372Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:d2194667ac719920688b87812fc13e6b01cb71b272b1fcbf1274c4468680972b","observation_id":"841edcc5-8c92-495f-a6cf-af03e6ef06ad","resolution":{"observed_at":"2026-08-14T12:37:23.384379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.363219Z","title":"Theory of reproducing kernels,","venue":null,"work_id":"91f40578-889e-407b-8be0-577569e67cb8","year":1950},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.500873Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:72e5ab86f0652041c65846c771cef3e3fdd24b010cbe02060003fb3a543d010b","observation_id":"506acee9-0f61-4971-a5f9-4cfb54e26fb9","resolution":{"observed_at":"2026-08-14T12:37:23.368113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.348420Z","title":"Kreyszig, Introductory functional analysis with applications","venue":null,"work_id":"e246120e-025d-4396-98a4-d715e8483016","year":1989},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.505627Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:129a35aa6d54ff6e57681a4578659c7d08786cb825789ca43d13d23028516dd6","observation_id":"f8dc2bac-a160-4107-ab20-9c91033530bf","resolution":{"observed_at":"2026-08-14T12:37:23.353013Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.333257Z","title":"Steinwart and A","venue":null,"work_id":"389646df-752d-4b07-93f1-0344419ca667","year":2008},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.510408Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:346755e54d26a302eddaba28ae0f2370e53f98335d88f4cfaad14cacc034edb3","observation_id":"9ba76fe3-8e7a-4daa-ac1d-a51fb36ae979","resolution":{"observed_at":"2026-08-14T12:37:23.338102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.317771Z","title":null,"venue":null,"work_id":"cc28fcfa-ed4b-44df-b48a-82499d6a6c1a","year":1995},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.514903Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:cd1584bcfefa684dee39fa721f8a16ec360f04350102e0a64f075b037c5e9309","observation_id":"ee7ed821-e545-40cd-b985-70a9172f2d9b","resolution":{"observed_at":"2026-08-14T12:37:23.322798Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.304648Z","title":"Schölkopf and A","venue":null,"work_id":"9ad38af4-b40d-47e5-8a9b-acc68f82923e","year":2001},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.519637Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:0d9b958cb258b814535ce24ac6472523ca949649c6a1690118c391766f07ed68","observation_id":"67d0b7fa-d80f-46de-b756-db4903271709","resolution":{"observed_at":"2026-08-14T12:37:23.308700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.524111Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.524111Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:224c0d22e341517a1f87f4e8549f295cfcdac114aee3c14199738eda66a568a1","observation_id":"ea3e250e-ecae-4676-a46e-17c45888aee2","resolution":{"observed_at":"2026-08-14T12:37:22.524111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.280485Z","title":"Nonlinear hyperspectral mixture analysis for tree cover estimates in orchards,","venue":null,"work_id":"e850a58a-a60b-4c11-928a-4bceee9f34fb","year":2009},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.528686Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:8dc4fe90a7b7280c47e872a57e925b43e9046bccc984d6b238a547ab479c801f","observation_id":"f495784d-0e97-4c14-9662-a0f249269c69","resolution":{"observed_at":"2026-08-14T12:37:23.285197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.266282Z","title":null,"venue":null,"work_id":"841a67b5-064c-45a2-841a-fc5635d6e1f4","year":2002},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.533510Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:e2e2456232e18f264568664bf81b4a4fbbef6555bcc6f1be737a5995d8b89521","observation_id":"19becc5d-ae2e-4062-9797-4ee185e4dfa4","resolution":{"observed_at":"2026-08-14T12:37:23.270795Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.251227Z","title":"Spectral-density- based graph construction techniques for hyperspectral image analysis,","venue":null,"work_id":"7dd5c502-f5be-4d83-b2b6-f05cdcbe43dd","year":2017},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.543328Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:dbe6c840bb195226221bd38a7c5446418cf3cfaf626563798f068ed8cae369fc","observation_id":"bd11f204-bb4f-47a2-9182-60c3339b61a3","resolution":{"observed_at":"2026-08-14T12:37:23.255939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.236360Z","title":"SLIC superpixels compared to state-of-the-art superpixel methods,","venue":null,"work_id":"c8745a74-b17b-4595-ab34-daa711304914","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.547911Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:65fa5183fe1a3b02478b4c6956d6df75ec1cf831e021e8f7c5c22406ee178d13","observation_id":"05ee6025-2fbd-4749-aa02-78b3fc8ba70d","resolution":{"observed_at":"2026-08-14T12:37:23.241282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.221758Z","title":"Boundary extraction in natural images using ultrametric contour maps,","venue":null,"work_id":"b9057133-4472-4ea6-9eb4-99a0577ee4ad","year":2006},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.552340Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:ab68dd9d082ddb998567968c5ffd515adafc4eca84e6ad8ffa6751aca3c5a45e","observation_id":"98a48270-beb5-4477-bb39-2e9d1890065e","resolution":{"observed_at":"2026-08-14T12:37:23.226563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.207005Z","title":"Hyperspectral image segmentation using a new spectral unmixing-based binary partition tree representation,","venue":null,"work_id":"b033d934-2830-4167-b845-c28d24825164","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.556639Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:9ed0155932c5c29dc2ee08a70e84366044fa747e6bec7cc905f7d409989f78f8","observation_id":"25c421ba-c378-4e68-a073-7206d5047135","resolution":{"observed_at":"2026-08-14T12:37:23.211782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.193088Z","title":"Spatial group sparsity reg- ularized nonnegative matrix factorization for hyperspectral unmixing,","venue":null,"work_id":"ed56a595-4b1e-4832-861c-cebd1369e418","year":2017},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.560722Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:13ddb4eb98a4e718ffd6480eaa6e1b01bd7e1276d52e2113329f338f4f20a77b","observation_id":"2e3dabaf-9876-4183-bfcc-a4ea55f9f986","resolution":{"observed_at":"2026-08-14T12:37:23.197590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.178484Z","title":"Generalized cross-validation as a method for choosing a good ridge parameter,","venue":null,"work_id":"a25fa8f1-d841-49fa-9df4-91a2148565ab","year":1979},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.564498Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:f8e51dc72476768c75a46f8025aaf9915eefc8c0659326edbe028f1728b1f5b7","observation_id":"c598dc20-38e4-429a-a5c6-cbe893c52005","resolution":{"observed_at":"2026-08-14T12:37:23.183169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.162850Z","title":"Stein Unbiased GrA- dient estimator of the Risk (SUGAR) for multiple parameter selection,","venue":null,"work_id":"0dd3466e-5646-4f72-addb-13b5f6ddcea9","year":2014},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.569125Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:ffec145c266efd71915f51ff1f81f163c68881a66d3630b574ca137ffd6b5f2a","observation_id":"876b7899-04c2-4b32-be9a-fca64b12725f","resolution":{"observed_at":"2026-08-14T12:37:23.168343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.147830Z","title":"ADA-PT: An adaptive parameter tuning strategy based on the weighted stein unbiased risk estimator,","venue":null,"work_id":"7b3227bf-5955-47e1-afe7-4a070d1ec5d1","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.573790Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:0d943349b8bc9028773731e11bd5421d815713c7af407a46699253c7f06f1248","observation_id":"3af23e6c-ac58-4371-a5de-f5a9677a74e3","resolution":{"observed_at":"2026-08-14T12:37:23.153267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.132948Z","title":"Efﬁcient determination of multiple regularization parameters in a generalized L-curve framework,","venue":null,"work_id":"cb75ed0c-6768-4ad4-9dfb-8820a073dbcf","year":2002},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.579470Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:d6973d993312940322fb104797ed189ff797a3ce6b012564247011ac9d04d479","observation_id":"0f6556d9-b7fc-47ab-be7c-b1bc44a28675","resolution":{"observed_at":"2026-08-14T12:37:23.137817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.117620Z","title":"Common structure of techniques for choosing smoothing parameters in regression problems,","venue":null,"work_id":"429b1630-6df9-40aa-9a33-cca56c8687a7","year":1987},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.584325Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:13d56eb40d13c4eead33839f2dd3947097eaa124e0840055772ce40586cb6885","observation_id":"a4e531af-d0df-4de5-b454-ace01e5e25d0","resolution":{"observed_at":"2026-08-14T12:37:23.123071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.101412Z","title":"A study of methods of choosing the smoothing parameter in image restoration by regularization,","venue":null,"work_id":"971f3082-855d-4997-89ef-5ac4b6df3428","year":1991},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.589057Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:d31e2deef30bc519c37aac2178932206ea1fcfdf0b47b4f1c2c02a0ee62c1441","observation_id":"216f1295-cb84-4de1-8bc6-4faa5fd0c5c4","resolution":{"observed_at":"2026-08-14T12:37:23.107220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.085295Z","title":"Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation,","venue":null,"work_id":"8f07b0be-acaa-461d-9dbb-09520825318b","year":1992},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.593818Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:e3f8a7f59c8c10aa8188cac747c4717483c0739437974d2d1807498c9324b293","observation_id":"abf3ff2f-6919-4c5e-af58-bb82319e6342","resolution":{"observed_at":"2026-08-14T12:37:23.089651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.071196Z","title":null,"venue":null,"work_id":"a42400fc-8248-4a18-886d-722e8301c60a","year":1996},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.598514Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:e053d38c93a62ef20bb2ae6f9e7da4fc256bb27721575d54e1aa813f6cf408f0","observation_id":"abb77dc9-b3ab-451a-bf39-46a6507e7ac1","resolution":{"observed_at":"2026-08-14T12:37:23.075422Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.056056Z","title":"The application of constrained least squares estimation to image restoration by digital computer,","venue":null,"work_id":"eb7e707a-94a3-477a-859d-4a67240fd753","year":1973},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.603094Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:a45428399d12aea00083728e16eb3e00327519856686fd4126f4178c3c9fcd3c","observation_id":"0dcbf6ed-a358-481d-8c59-4b4cd0f01236","resolution":{"observed_at":"2026-08-14T12:37:23.060837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.040673Z","title":"Bayesian nonlinear hyperspectral unmixing with spatial residual component analysis,","venue":null,"work_id":"b7f40ba3-d9a0-4b55-bf81-8baa952a254d","year":2015},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.608017Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:2092036674308ac32e1e91225aa3d731c21fbbbf0a85383377d2be520bdaea7c","observation_id":"4b43abf0-9a8b-43b1-a355-fa6138557f06","resolution":{"observed_at":"2026-08-14T12:37:23.045661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:23.025685Z","title":"Spatial regularization for nonlinear unmixing of hyperspectral data with vector- valued kernel functions,","venue":null,"work_id":"b6f4da95-f96e-4661-8271-04f47850b8d1","year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.612769Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:6b8c39c4ea263826b77ad7ebf99f24aa31149339909b177b2cccb8cb061b3d49","observation_id":"3d83946f-d380-40f7-a24e-e8538fbee452","resolution":{"observed_at":"2026-08-14T12:37:23.030645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.617447Z","title":"Boyd and L","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.617447Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:a22ab8f0fdcff080a793e2fba2f25e6f6cfc9e16499da8b9c60070d3c0f1b4fc","observation_id":"7ac33ff3-586f-4d81-8077-2f9b32360b1b","resolution":{"observed_at":"2026-08-14T12:37:22.617447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.999480Z","title":"Generalized S-lemma and strong duality in nonconvex quadratic programming,","venue":null,"work_id":"31a74cf6-63e6-49ee-8c7e-94abb375f907","year":2013},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.622086Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:eb83f441d8b09d15503a95754ca0a9f1163e1b0c0048de7a33b1a8ddf09a6371","observation_id":"389c08e4-1652-4c84-b804-128fd6fdcaad","resolution":{"observed_at":"2026-08-14T12:37:23.004382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"cited_work":{"arxiv_id":"1908.06925","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.06925","snapshot_observed_at":"2026-08-14T12:37:22.706911Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","venue":"eess.IV","work_id":"6bcb5918-c294-439c-8cb2-b4159e061581","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.626754Z"},"links":{"cited_paper":"/paper/1908.06925","citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:441bb497c27b8513b16bed2f96a9dad9e793a6bbaf13d9b7e56a649ab7d7e799","observation_id":"d9454fa9-6714-47a0-a34e-8cb6a858c638","resolution":{"observed_at":"2026-08-14T12:37:22.713895Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.983875Z","title":"The multivariate bisection algorithm,","venue":null,"work_id":"f28e5df7-dcf5-4680-9c95-d77ae95104ee","year":2019},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.631779Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:8313bfd8ac0b26f7b10d5f1718ee3610f4bf0b7c9b634fee5226c1cd5e86cb28","observation_id":"256d49a7-e63f-4694-9a2a-a78590badf70","resolution":{"observed_at":"2026-08-14T12:37:22.988711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.969251Z","title":"Bisection method in higher dimensions and the efﬁciency number,","venue":null,"work_id":"62d30d3a-7565-4e11-9a94-2cc7a0cf2ebf","year":2012},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.636218Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:853fd108c2d9333d613601eb440b84221bdf56b70f4f6ce323f08ac63e33d8bf","observation_id":"00430881-745c-4112-9182-145b6009f14f","resolution":{"observed_at":"2026-08-14T12:37:22.974079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.954211Z","title":"Low-dimensional enhanced superpixel representation with homogeneity testing for unmixing of hyperspectral imagery,","venue":null,"work_id":"4b1bee7f-05e4-461d-911c-6a1135c1cd68","year":2018},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.640937Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:45a50a0451fc2354ca80f2654b8a89541263d1ebc1af6e58aa3018c36fd9441a","observation_id":"708bae1a-556d-43bf-ad71-1d0e4c6f88a8","resolution":{"observed_at":"2026-08-14T12:37:22.959039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.938524Z","title":"Hyperspectral unmixing in presence of endmember variability, nonlinearity, or mismodeling effects,","venue":null,"work_id":"c84205d8-0898-4a56-af0e-c57ac769976d","year":2016},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.645866Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:a0ecf2e63493f249668779adfcb42a6dfbec766fb5a16df7c53128b3b68594fd","observation_id":"ab077eb4-bc18-4ff8-828c-7ab1fedb0ffe","resolution":{"observed_at":"2026-08-14T12:37:22.943391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.923301Z","title":"Principal components transform with simple, automatic noise adjustment,","venue":null,"work_id":"21ed21c3-2bd6-43ae-9554-ea8d650491a2","year":1996},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.649937Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:6c36f3a8efd2ce3b899b24dfcbfa52c4a51542bef1343f6a9db560193187f6db","observation_id":"9e70cdfd-266f-440c-868b-2bb40321bfa2","resolution":{"observed_at":"2026-08-14T12:37:22.928345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.907227Z","title":"Modiﬁed residual method for the estimation of noise in hyperspectral images","venue":null,"work_id":"f6d74918-0de8-4733-a29d-0598d498739d","year":2017},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.653880Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:4b9b9980c66759d22f198085f685250eca6f1ea508f3e8b03d88fde7180b83ee","observation_id":"4242f246-177b-472f-b4f8-58866ad9c98b","resolution":{"observed_at":"2026-08-14T12:37:22.912727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.890957Z","title":"Vertex Component Anal- ysis: A fast algorithm to unmix hyperspectral data,","venue":null,"work_id":"1f15896c-2a7c-48c2-9fed-93bb371d6255","year":2005},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.657994Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:990d8f5b00a3187a2817f0244694290242861218b705fa815850f6b94c7c5b79","observation_id":"ec0dd0eb-1fa0-4aed-88a2-670ffeb63a1f","resolution":{"observed_at":"2026-08-14T12:37:22.896355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.875565Z","title":"Strong duality for the CDT subproblem: a necessary and sufﬁcient condition,","venue":null,"work_id":"329ce072-c187-4e30-ab07-1c06cc342a5a","year":2009},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.662117Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:5e888b8a97fde2558310aaafdb6be1b3913268257baecf321e612e2cd87c7ab7","observation_id":"77fe6668-a75b-4f78-b156-befb135db455","resolution":{"observed_at":"2026-08-14T12:37:22.880620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:37:22.666794Z","title":"Copositive relaxation beats Lagrangian dual bounds in quadratically and linearly constrained quadratic optimization problems,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing","version":3},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-14T12:37:22.666794Z"},"links":{"citing_paper":"/paper/1908.06925"},"observation_digest":"sha256:b2a862bf0bd5a9d4e2933d76f13acaf3f4a54d3ddf7e861f3b8bff01193a1c05","observation_id":"e6196b93-0a83-4203-905d-c32b6443634e","resolution":{"observed_at":"2026-08-14T12:37:22.666794Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"1908.06925","last_updated":"2020-03-02T19:31:46Z","latest_version":3,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-14T19:32:58.685007Z","submitted_at":"2019-08-19T16:52:14Z","title":"A Blind Multiscale Spatial Regularization Framework for Kernel-based Spectral Unmixing"},"reference_resolution":{"displayed":79,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":1,"verified_fuzzy":69},"total_outbound_references":79},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 1 inbound Pith citation observation for arXiv:1908.06925."}