{"as_of":"2026-08-16T06:25:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:80fad9e4cd62f620d3265f7652dd935667f9a2ac90df6c8cd3b531991a0dd703","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:47:34.510935Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.08223/citation-record","integrity":"/paper/1908.08223/integrity","json":"/paper/1908.08223/citation-record.json","paper":"/paper/1908.08223"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:47:34.844660Z","title":"Deepglobe 2018: A challeng e to parse the earth through satellite images,","venue":null,"work_id":"a4f8bd63-3ac6-449d-9cab-889f8eada204","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.408741Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:536df53309e37263648ebfff19eb6d65bb90a669e0387a6b91ffc1726206d136","observation_id":"89958e28-8587-4e38-a597-3fb95f8cd282","resolution":{"observed_at":"2026-08-14T11:47:34.848480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.833971Z","title":"A computational approach to edge detection,","venue":null,"work_id":"b87ba559-1f59-4aa0-b1a0-9609abfc0152","year":1986},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.412811Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:fdf0a34b39f305e53c941f56d0332cbe46f98ef11bbaa72c20db213628734d05","observation_id":"55147356-5989-4f7c-9352-326698d9d399","resolution":{"observed_at":"2026-08-14T11:47:34.837717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.822207Z","title":"Use of the hough transformation to detect lines and curves in pictures","venue":null,"work_id":"523addb6-aeec-446e-877b-54a1f7756db1","year":1972},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.416417Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:8146f48bf9054874b668536c888ae41c3e742c6931405f482e8ef844375c10d6","observation_id":"e7e981d8-d460-43ee-8405-9e93137b4129","resolution":{"observed_at":"2026-08-14T11:47:34.826408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.811077Z","title":"Detection of linear features in sar images: Application to road network extraction,","venue":null,"work_id":"c3d3601e-bf21-4d26-b77d-350d964e1fe3","year":1998},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.420312Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:9a066c9c29013a5ab0d8a608e05cbe82efbcef6f9cad1da90569ae3577d07be0","observation_id":"5c48cd7f-e6de-49ce-8058-1323b815a9e5","resolution":{"observed_at":"2026-08-14T11:47:34.815038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.800285Z","title":"Road extraction usi ng svm and image segmentation,","venue":null,"work_id":"4aa183c1-3964-4af6-b271-b40720ec436b","year":2004},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.424762Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:c3172b5f36e5355f51583b7e23a4e64b09fe84a8d8c0491aabab276eba80e1ed","observation_id":"c2b012a2-30a5-4992-9be2-8e91d53d5256","resolution":{"observed_at":"2026-08-14T11:47:34.804153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.790018Z","title":"Fully convolutio nal networks for semantic segmentation,","venue":null,"work_id":"b30c4e50-ff7c-4b9e-b708-f06b866e733e","year":2015},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.428432Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:aa9d75a06191b2d5e5fce9215f48f8b1ac6d86fc58a57bd41b715b9cacddf9f2","observation_id":"7facf68a-3d63-4239-be87-ca7a12b4d086","resolution":{"observed_at":"2026-08-14T11:47:34.793706Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.779659Z","title":"Road structure refined cnn for r oad extraction in aerial image,","venue":null,"work_id":"98736922-cb4b-45e3-a2c8-11aa58830048","year":2017},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.432333Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:30c35a2701a54fd2b1778cd45c9c56a430be00cc7672ee478d56e1534c835fb8","observation_id":"890ccf12-7682-41fc-b184-6f052cd88b9e","resolution":{"observed_at":"2026-08-14T11:47:34.783410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.769061Z","title":"Pednet: A spa tio- temporal deep convolutional neural network for pedestrian segmenta- tion,","venue":null,"work_id":"7753bf49-c0e4-4ea8-bf21-651bfba85c85","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.435749Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:cc795880873915fc0d944e137affef9fb6864f8d39d70cd0f58c0375513f76c1","observation_id":"9bf3556f-23fa-43d9-8a45-ace6dde280ca","resolution":{"observed_at":"2026-08-14T11:47:34.772916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.758676Z","title":"The one hundred layers tiramisu: Fully convolutional densenet s for semantic segmentation,","venue":null,"work_id":"169f7291-448c-4093-b84d-5ddcb28dad6c","year":2017},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.439235Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:3fdd3fb4277ff5aa0cf697d8fe8503962e6dbdb540bee4cd77a07a568cf7a995","observation_id":"707209e1-cb2b-4ae5-abfc-4fb87d76b308","resolution":{"observed_at":"2026-08-14T11:47:34.762314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.748106Z","title":"Road extraction by deep re sidual u- net,","venue":null,"work_id":"9d94de5e-1bf5-49d6-bacf-1e0bdb500ff0","year":2015},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.442707Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:d34b8f4a77bce50672c93809b7ee0f321a28db7a9c1c03add7369f64a30cc03b","observation_id":"a160809f-2e1e-47f3-ad16-a015101a2ab3","resolution":{"observed_at":"2026-08-14T11:47:34.751864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.737751Z","title":"Linknet: Exploiting encod er represen- tations for efficient semantic segmentation,","venue":null,"work_id":"a6df6d59-df7c-4b5e-9d27-def6fdd9fdec","year":2017},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.446184Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:f888a314e5c73c08baf76a02f20705c0c111559bb15b2be58c70cfbe81621450","observation_id":"41a8b9d5-cfa6-4288-89c5-5d0345112db2","resolution":{"observed_at":"2026-08-14T11:47:34.741470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.726935Z","title":"D-linknet: Linknet with pre trained encoder and dilated convolution for high resolution satell ite imagery road extraction,","venue":null,"work_id":"f30967ad-b00c-45cd-88c3-ec02ac5b0a96","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.449670Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:88a3cb5911722b6f12e1ac95f8c8c137a39496c0366f48204bbbd4791da9e0cd","observation_id":"63d65462-a7d1-4a86-b8ec-b47ed0c28147","resolution":{"observed_at":"2026-08-14T11:47:34.731028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.715673Z","title":"Deepglobe 2018: A challen ge to parse the earth through satellite images,","venue":null,"work_id":"719f44bf-d2ce-4dee-b085-e47777496255","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.453189Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:1ce7f756b5e21f1d848b1c5c0b28714232459b2ce736ae7dcc034997393da568","observation_id":"44e208b5-aaca-44ae-8703-0ee652fa2b05","resolution":{"observed_at":"2026-08-14T11:47:34.719883Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.05587","last_updated":"2017-12-05T18:06:21Z","snapshot_observed_at":"2026-08-07T13:44:53.690521Z","submitted_at":"2017-06-17T22:48:57Z","title":"Rethinking Atrous Convolution for Semantic Image Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.05587","snapshot_observed_at":"2026-08-14T11:47:34.456528Z","title":"Ret hinking atrous convolution for semantic image segmentation,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.456528Z"},"links":{"cited_paper":"/paper/1706.05587","citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:0add1a1a029a0e9272c91dfbcf2c1704dddbc75c00a3d970bdbefcda3e08f0ee","observation_id":"8ab37365-c8ec-4a1b-a94f-dc54fd6aa35f","resolution":{"observed_at":"2026-08-14T11:47:34.456528Z","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":"2026-08-14T11:47:34.703957Z","title":"Encoder- decoder with atrous separable convolution for semantic ima ge segmen- tation,","venue":null,"work_id":"8379e1a8-a0dd-4220-8b08-9adc8b85bab5","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.460198Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:407b2939cbe992c9a0f1085178a1b2c2c1657fe21969f08c28aad6d4d12dd202","observation_id":"5c9332ea-2e57-4284-9be3-15aebebf50d2","resolution":{"observed_at":"2026-08-14T11:47:34.708412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.06211","last_updated":"2017-06-05T10:08:50Z","snapshot_observed_at":"2026-08-15T09:26:38.760137Z","submitted_at":"2017-03-17T21:58:20Z","title":"Deformable Convolutional Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.06211","snapshot_observed_at":"2026-08-14T11:47:34.463422Z","title":"Deformable convolutional networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.463422Z"},"links":{"cited_paper":"/paper/1703.06211","citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:f2222a6448bcae54e12b823169e6b8ac3d8b9a6e80e28f23d0efba8567e7cca1","observation_id":"a07ba973-641d-4655-b6d9-4f7638cc59fa","resolution":{"observed_at":"2026-08-14T11:47:34.463422Z","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":"2026-08-14T11:47:34.692708Z","title":"Psanet: Point-wise spatial attention network for scene parsing,","venue":null,"work_id":"7729e121-dc57-452d-9ff9-fe830ac54b69","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.467226Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:50465bbdf1799b0bc37a59579dd20cdf8478ad9e578cabf0a11d8bdb13f89173","observation_id":"d1c2b2c9-5053-4218-9d2e-1d808ab9d86e","resolution":{"observed_at":"2026-08-14T11:47:34.696590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12150","last_updated":"2018-11-29T14:05:04Z","snapshot_observed_at":"2026-08-14T17:51:21.454794Z","submitted_at":"2018-11-29T14:05:04Z","title":"Parameter-Free Spatial Attention Network for Person Re-Identification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12150","snapshot_observed_at":"2026-08-14T11:47:34.470652Z","title":"Parame ter-free spatial attention network for person re-identification,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.470652Z"},"links":{"cited_paper":"/paper/1811.12150","citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:e5de51572b00b3ed1d94a0778774ee3d89a3f49be2aa9da41169869022cfecac","observation_id":"90756257-7d0b-4ba0-9858-456592c6effa","resolution":{"observed_at":"2026-08-14T11:47:34.470652Z","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":"2026-08-14T11:47:34.681590Z","title":"Visual sp atial attention network for relationship detection,","venue":null,"work_id":"19ab6e2f-9dc9-43b1-8771-3c7f3c426e3e","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.474548Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:904b0cccc9a4c2b80f8ebc9513585809d38a49b1578e2de8f24e0421087ebc5f","observation_id":"d91155a6-811e-4a29-823c-cf51c0e3065c","resolution":{"observed_at":"2026-08-14T11:47:34.685297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.671067Z","title":"Understanding t he effective receptive field in deep convolutional neural networks,","venue":null,"work_id":"3c127e88-1223-4370-960e-1a7b970a6859","year":2016},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.478047Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:775faba9bc45dd14df5a01a69cb136da6ec21237839d13c5b16afa7a49bb15a9","observation_id":"59b00b18-eec3-4509-91d8-e23faef819db","resolution":{"observed_at":"2026-08-14T11:47:34.674822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.660415Z","title":"Non-local neu ral net- works,","venue":null,"work_id":"6e2d4f86-cd88-44dc-acda-8267e273d654","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.482060Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:877a740cda3de8bbb1e39decbce0c046affab0eabd3b8de089fc6f2119baf442","observation_id":"89c09e0e-af9c-4a87-9598-ef234ebfd942","resolution":{"observed_at":"2026-08-14T11:47:34.663873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.648899Z","title":"Residual non -local attention networks for image restoration,","venue":null,"work_id":"3a6e02c8-ac88-413f-a92a-edb3efca5b97","year":2019},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.485741Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:eaf217d53f3d11a368cc67f524af0db159a260d8b4e1ae75939b524a9661124b","observation_id":"8258eae4-23e4-47d3-afb7-7c39c6acbde4","resolution":{"observed_at":"2026-08-14T11:47:34.652702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.638237Z","title":"Deep residual learni ng for image recognition,","venue":null,"work_id":"ffdd8b83-66ef-4e41-8c41-d025739ed08e","year":2016},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.489381Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:c5cf81e433c65629be8b2f5c67cb66bbbe2b58ac6324457bbe728bbef6bab538","observation_id":"1bc0f805-60cd-4254-aec2-a1bdda5c1cf8","resolution":{"observed_at":"2026-08-14T11:47:34.642026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.626758Z","title":"Adam: A method for stochastic opt imization,","venue":null,"work_id":"0363d805-91d6-438a-afcd-b5a12d87ae72","year":2015},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.492987Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:60468c53ee71d951c2490a19aae8b7e05777cc2d8868845a78b0d7d80989a69b","observation_id":"5daa1987-9855-4a53-a375-fd86ae586fa4","resolution":{"observed_at":"2026-08-14T11:47:34.630864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.615213Z","title":"A non-local algori thm for image denoising,","venue":null,"work_id":"26c71a49-f543-4e83-9d5e-29f4bc8edfeb","year":2005},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.496431Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:941fd6b0a7b658726e408d95dd689d034bdf0957391a45f0f226a6fbfebb8634","observation_id":"c1c36b90-92ab-440b-8ee0-73758a3047cf","resolution":{"observed_at":"2026-08-14T11:47:34.619192Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.603905Z","title":"Road detection w ith eosresunet and post vectorizing algorithm,","venue":null,"work_id":"96c2377d-c04a-438c-86b6-1b7e6901ad39","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.500114Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:da256ba0196c03e8e7799e667f07e27f076ae55bb3c0f9625062af2768791710","observation_id":"52c829e1-a5f5-4dfa-ab4f-57f4f5c20fc8","resolution":{"observed_at":"2026-08-14T11:47:34.607771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.592619Z","title":"Stacked u-nets with mu lti-output for road extraction,","venue":null,"work_id":"57ba3d72-08bd-482b-9a84-bead9a8a6774","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.503782Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:a8d3b12b6e2521cca2da96aafaa492b774b6240b350cc1e08aa872f60e56426f","observation_id":"bee7b080-a5c8-4611-a701-ba913765d908","resolution":{"observed_at":"2026-08-14T11:47:34.596394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.582067Z","title":"Residual inception skip network for binary s egmentation,","venue":null,"work_id":"d1bca925-cef4-416f-b11a-5476337d0acd","year":2018},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.507258Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:655e8eb5b00d38a918a883a59afa15914bf0b228bca883fbf896bcc2e1ec2a54","observation_id":"a43cf308-76c2-4ffe-a8c6-e01ffafceb0e","resolution":{"observed_at":"2026-08-14T11:47:34.585783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T11:47:34.568614Z","title":"Fully convolution al networks for building and road extraction: Preliminary results,","venue":null,"work_id":"3fb3d344-84b8-4833-a5e4-e630bd6cf1e4","year":2016},"citing_paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:47:34.510935Z"},"links":{"citing_paper":"/paper/1908.08223"},"observation_digest":"sha256:3122250b518a0169b237a05c4d8f4a617afc82c242182cbef4c045434a57ae20","observation_id":"d84c0f51-8de0-435b-b8a7-bf36f88e97fe","resolution":{"observed_at":"2026-08-14T11:47:34.574719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.08223","last_updated":"2020-11-11T10:25:37Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T02:22:55.013718Z","submitted_at":"2019-08-22T06:56:57Z","title":"NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":26},"total_outbound_references":29},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:1908.08223."}