{"as_of":"2026-08-22T13:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6216af962d266dba2e73c837aa6261d3cd590428388cb7bd0ffbc841ecaabc2e","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:10:48.947999Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+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/2501.06053/citation-record","integrity":"/paper/2501.06053/integrity","json":"/paper/2501.06053/citation-record.json","paper":"/paper/2501.06053"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:10:49.849273Z","title":"Ship detection in spaceborne infrared image based on lightweight cnn and multisource feature cascade decision,","venue":null,"work_id":"5b80aa48-b9ae-4b1e-98a8-aa909de0049d","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.611737Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:9ceffb270f0c9d5fc953c0b41194240c4804f98c3649a7865931b7536ee984a0","observation_id":"03e7adf4-8a11-4643-9b86-d1d264f8e2cc","resolution":{"observed_at":"2026-08-10T21:10:49.853967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.837480Z","title":"Fishing vessel classification in sar images using a novel deep learning model,","venue":null,"work_id":"0ba5f521-6602-495d-89f4-c20d72349ff3","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.617104Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:aa3fd94e61dcc765b002ca01234b88677c84fcff18a9729553b10196e0e9b48c","observation_id":"f5fa73cf-99e7-4e02-a13b-be8cfcb94048","resolution":{"observed_at":"2026-08-10T21:10:49.841551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.824214Z","title":"Ship detection based on complex signal kurtosis in single-channel sar imagery,","venue":null,"work_id":"5a0e37dd-40a5-421c-a7d0-9e98c9670f17","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.625625Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:0f4d696d5f6a9bd5fb1c785b0ccc4a703d7850e11878946aa43924af3ff40a5d","observation_id":"63a28c03-e6d5-4cf3-87ba-4fc5a6a12779","resolution":{"observed_at":"2026-08-10T21:10:49.828502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.812204Z","title":"Git: Graph interactive transformer for vehicle re-identification,","venue":null,"work_id":"d0764402-222f-418e-8550-354e34a5e1ac","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.630291Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:a013119ee4cdcc209408a52d92d3ca76891a00c8234a6be1d775c26c452ca887","observation_id":"222bb89c-999e-4397-bc6d-222b1cdc4b61","resolution":{"observed_at":"2026-08-10T21:10:49.816151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.799992Z","title":"Sar ship detection based on explainable evidence learning under intraclass imbalance,","venue":null,"work_id":"9efa86cc-409b-40c8-8972-b05db53bad91","year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.634599Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:8b9ba6e2c336f3daee42f45010935ffefa0e018c54d9d44d6763deca6f68c970","observation_id":"fff6b3f3-43ad-4bdf-9e74-9aac67324362","resolution":{"observed_at":"2026-08-10T21:10:49.804625Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.787853Z","title":"Oriented gaussian function- based box boundary-aware vectors for oriented ship detection in mul- tiresolution sar imagery,","venue":null,"work_id":"a1684cf1-95e4-4007-a07b-22a1eef8494d","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.638885Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:269f27ccd933170b25882598e37affe2344fb04f2ce53d01bd0ea846fb8b088f","observation_id":"1e4da2ea-1aac-40f7-b738-2dd03d541578","resolution":{"observed_at":"2026-08-10T21:10:49.792066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.775356Z","title":"An adaptive and fast cfar algorithm based on automatic censoring for target detection in high- resolution sar images,","venue":null,"work_id":"53026cc3-fbd8-400b-9bc7-7334e30db967","year":2009},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.643353Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:c7626995973c6da0d2dd02b69a2f4d9e75fedb20b6dedd0543fe93bf01cb6335","observation_id":"ad6a87c0-18b1-43a5-a6ef-a03d1aa402fa","resolution":{"observed_at":"2026-08-10T21:10:49.779382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.762200Z","title":"Ship detection in sar images based on lognormal ρ -metric,","venue":null,"work_id":"24fd4bab-b3c4-4366-a55f-ada4b31e1010","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.674748Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:9150a0c17ba3868eb6dfaee92429210e0e18673fb60698bfd743d41d05e2cc9b","observation_id":"854f8e7e-5523-4d04-a36c-b4a9d4e6a362","resolution":{"observed_at":"2026-08-10T21:10:49.766855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.748493Z","title":"Analysis of the ship target detection in high-resolution sar images based on information theory and harris corner detection,","venue":null,"work_id":"c3dc7c08-b5f4-4568-9938-d2acaf5df140","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.689899Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:6fee1de063601904dbd4f6ddd56260d63fc150bc8bbc0259f22f0eff4537c594","observation_id":"e4f7c20a-388c-487f-9c26-28cd2f4bde17","resolution":{"observed_at":"2026-08-10T21:10:49.752866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.736215Z","title":"A novel algorithm for ship detection in sar imagery based on the wavelet transform,","venue":null,"work_id":"f1fb85a2-9c95-4804-a113-d02903116f04","year":2005},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.694862Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:8df802c312bd39c20f9dd7dfb3b49ce456c2f80b7c4272c625f08e7937c6af09","observation_id":"f8cc92b2-c510-497f-bf49-7114d65303c4","resolution":{"observed_at":"2026-08-10T21:10:49.740719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.724065Z","title":"A novel ship detection method based on gradient and integral feature for single-polarization synthetic aperture radar imagery,","venue":null,"work_id":"72d3b324-6002-4473-b2aa-f3fc97c2f5b2","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.705797Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:7235e55f6b13211fb1efcf3c4db4ad606fcf6e83e3c90803dd61ce5b6e2215c2","observation_id":"a22e2265-a61a-4642-b23e-5641af789f73","resolution":{"observed_at":"2026-08-10T21:10:49.728169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.711071Z","title":"An improved bilateral cfar ship detection algorithm for sar image in complex envi- ronment,","venue":null,"work_id":"861af780-7ffc-4ddc-aeae-445bd36dcde3","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.714764Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d04727b6ce33cbb85216396387a191fccb73385d455efa11f6100503b0a9c50d","observation_id":"15b8f093-99f4-49b4-bdf2-795b33a43f5c","resolution":{"observed_at":"2026-08-10T21:10:49.715366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.697477Z","title":"A survey of convolutional neural networks: Analysis, applications, and prospects,","venue":null,"work_id":"72b777a3-6bc2-4d5d-a163-130300d2e9c7","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.724388Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:1f958068b21952a6e40a3e18b0fea76deb76309c281dc8926e1a36d578b6b904","observation_id":"9bf29bb1-1c1d-4ec3-b143-0beaa5581c37","resolution":{"observed_at":"2026-08-10T21:10:49.702611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.728802Z","title":"Faster r-cnn: Towards real-time object detection with region proposal networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.728802Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:c7d80ea1eaf24b5f9083d65285a8b53d016d18a06dbd089ef509abbd3a46a83e","observation_id":"897249c1-527a-488f-89dc-3e9e581e5d74","resolution":{"observed_at":"2026-08-10T21:10:48.728802Z","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":"2026-08-10T21:10:49.677591Z","title":"Enhancing landslide segmentation with guide attention mechanism and fast fourier transformer,","venue":null,"work_id":"d1a6516b-a206-4a97-93aa-22bd5587eb3e","year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.733533Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:5b086ccfe56e17bd3bbb95ba1ff352ee6579044a2e7e374f72ed7841331a0a21","observation_id":"f832a88f-96fb-43b1-9c51-72959e8e22e2","resolution":{"observed_at":"2026-08-10T21:10:49.681649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.664569Z","title":"Cascade r-cnn: Delving into high quality object detection,","venue":null,"work_id":"804db0c5-a183-41bd-a954-2425c64e9994","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.738066Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:ba5591ca287057ee39a04ac1f861f45db466729d14a5121d822d7115c80d68e0","observation_id":"6e75d871-4a14-4afa-bc9a-bd1c228265df","resolution":{"observed_at":"2026-08-10T21:10:49.669306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.652653Z","title":"Ssd: Single shot multibox detector,","venue":null,"work_id":"fd76cf90-4b3d-4aa4-babf-37a55cb224b7","year":2016},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.742663Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:ba4e34908c5f923245099e7eb6cfdb945e278283fccc839578ba9c3016d9e78e","observation_id":"e70b0954-2130-48a8-ae69-7c07f2554fa2","resolution":{"observed_at":"2026-08-10T21:10:49.656908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.639524Z","title":"You only look once: Unified, real-time object detection,","venue":null,"work_id":"5aa9908b-9e6a-4609-bde3-5df64bcad6cf","year":2016},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.746368Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:e50940f5cce7340f058775f494e84e2f983e27bb8b9e712546802ab1f03ff1b7","observation_id":"0ab5acf6-0888-4454-b346-171e13b60404","resolution":{"observed_at":"2026-08-10T21:10:49.643568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.627138Z","title":"Yolov3: An incremental improvement,","venue":null,"work_id":"618a1440-f30a-4673-abc5-655b25151cc2","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.750073Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:67eb587ace9bd42fa19771d6b7ee7222b22b4c268979f335d8c974dc2fcf19dc","observation_id":"ed3ed5d3-8fc2-4539-a0a5-351eca2dd418","resolution":{"observed_at":"2026-08-10T21:10:49.631425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.615211Z","title":"Yolov4: Optimal speed and accuracy of object detection,","venue":null,"work_id":"0bcb32dc-0544-47c1-9796-48d1431badfc","year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.754346Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:0fd7aff0f0ea92f405c02a5fd6a36cc2c870b68d882864d636127bc6c0114fdc","observation_id":"a8a28586-ece7-43d3-b581-dbd0fbdfa372","resolution":{"observed_at":"2026-08-10T21:10:49.619381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.603340Z","title":"Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,","venue":null,"work_id":"b124ed15-2e1e-406b-a976-9d27f6f3f913","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.758406Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:c9d27e97867491f3fb9eae9ac373dede053d6a41842bdf324f5a6229eef71695","observation_id":"eec3838f-fecb-407c-9724-16d273a689c6","resolution":{"observed_at":"2026-08-10T21:10:49.607544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.590885Z","title":"Yolox: Exceeding yolo series in 2021,","venue":null,"work_id":"9ff7ffb2-6751-4e7f-8d63-124d5d1f55dd","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.763185Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:67c6d0c5c9fbf0137e00a57b948119abad67fbff7b2effabf1a0ffe1c7a61543","observation_id":"3b0fe533-fe7a-42b8-abfe-f5a1028db1a5","resolution":{"observed_at":"2026-08-10T21:10:49.595339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.766871Z","title":"Focal loss for dense object detection,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.766871Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:dbc9a5cc197cfbbe86705668c01f241a2fb15dac6cccd8bbf1ff2848c1eb5426","observation_id":"390f6476-b973-4bb0-98d5-e4ba4ef18419","resolution":{"observed_at":"2026-08-10T21:10:48.766871Z","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":"2026-08-10T21:10:49.572062Z","title":"Fcos: Fully convolutional one- stage object detection,","venue":null,"work_id":"8c8586be-4ce6-495d-a4ac-0cea0b8b88b7","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.770654Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:e3c7cba4299fe313b424c0a8e1eb26824ae7cc6647afbfbcdc6ebed987b8b6eb","observation_id":"d2bc2eaf-b452-4bf6-9bd8-b32661586694","resolution":{"observed_at":"2026-08-10T21:10:49.576815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.560491Z","title":"Centernet: Keypoint triplets for object detection,","venue":null,"work_id":"d9499225-c28a-469e-b85a-c0723ff5a2ec","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.777714Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:8f07aca543d1c053b413aefbb7cd921f7b0b862f633be185d20326495873a510","observation_id":"0f410ac6-32e0-419d-bf8a-0b425226922a","resolution":{"observed_at":"2026-08-10T21:10:49.564445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.547161Z","title":"Ship detection in large-scale sar images via spatial shuffle-group enhance attention,","venue":null,"work_id":"6e156081-565c-4b2f-b17d-1ec9c21d4b21","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.781836Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:366d302d96b10d9a718fe7405bdcd46ab4c6982d2ac7b23345006931a475bee9","observation_id":"4dd5877f-09f6-4207-8c7f-3fd93858f8d8","resolution":{"observed_at":"2026-08-10T21:10:49.552329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.534358Z","title":"An improved deep neural network for small-ship detection in sar imagery,","venue":null,"work_id":"b05a3c92-9295-40f3-a2ed-4a1d300edb06","year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.785644Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:20f9c9e4356e5d8d60e1980d11c31daf593cba54dba325f8688617edd592a051","observation_id":"84c6d33f-e195-4c6e-b567-ca7fb1d0172a","resolution":{"observed_at":"2026-08-10T21:10:49.538495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.521800Z","title":"High-speed lightweight ship detection algorithm based on yolo-v4 for three-channels rgb sar image,","venue":null,"work_id":"6afa4e9c-fd74-4de5-84a3-3aa8e8e2aa87","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.791952Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:4f84d0ad69d47a448b319f9ebc2fc7143e5802efb5f1ff6449e7ffd754b9d1cf","observation_id":"79215663-e52b-455c-a5b4-683bc9e827b7","resolution":{"observed_at":"2026-08-10T21:10:49.526470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.507886Z","title":"Feature pyramid networks for object detection,","venue":null,"work_id":"c6df2d4d-c5eb-428f-b5a4-65760406fe3c","year":2017},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.795985Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:852c7bbb06c0d8add1239ae10f6b2933255457d7bca8d6d38317e0a50458868b","observation_id":"d164e3ca-8314-46f8-a4c6-e0f6f234bd00","resolution":{"observed_at":"2026-08-10T21:10:49.512285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.495114Z","title":"Path aggregation network for instance segmentation,","venue":null,"work_id":"6d5e01b5-b640-4b40-8dee-390efe6a3f99","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.799740Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:e81d9549ff7d5654bf616e2b10c50ed5bf0a271f136ed43662819c2340f96694","observation_id":"66e3dd21-dfb3-48bc-a07c-fc63817cabf6","resolution":{"observed_at":"2026-08-10T21:10:49.499243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.482639Z","title":"Ship detection in sar images based on an improved faster r-cnn,","venue":null,"work_id":"1d2727c6-bcf7-4204-bffa-0d4c4008bac6","year":2017},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.803559Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:f587be8985df4a5b891d29ab5d945fe2dcdfe276016713a16060af52652d342e","observation_id":"7663d16b-e600-4151-9ba1-ef5280b55175","resolution":{"observed_at":"2026-08-10T21:10:49.486630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.471135Z","title":"Hrsid: A high-resolution sar images dataset for ship detection and instance segmentation,","venue":null,"work_id":"e8725f94-3a9f-4892-8d2e-fe080cf3bdd2","year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.807350Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:568a3dd7b884d8059f4d462fae0cb5811eb213fc5958abfd95ec2a32b15b5ba5","observation_id":"1236ac63-eaa6-4770-92fc-4bb98bc7eefa","resolution":{"observed_at":"2026-08-10T21:10:49.475114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.460036Z","title":"Ls-ssdd-v1.0: A deep learning dataset dedicated to small ship detection from large-scale sentinel-1 sar images,","venue":null,"work_id":"6b216e68-eb12-4e61-93ae-a9758ebf9cfb","year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.811637Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:237d558ecbdd2b0efafc5a2d586acc7bedac23a666150764ea686e5e05f4e3b4","observation_id":"7a7e8cc0-1645-413f-ad15-ea0bc2647d4e","resolution":{"observed_at":"2026-08-10T21:10:49.464005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.448776Z","title":"Srt- net: Scattering region topology network for oriented ship detection in large-scale sar images,","venue":null,"work_id":"1ec0ce71-3f11-496e-9a9f-0f92c8d32c88","year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.816102Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:90e1efb54d42dc08fe215b39bc908067f693b0f94010f7893dbd1d623b6b135e","observation_id":"59a9534d-5677-490d-8b23-29e1221119fb","resolution":{"observed_at":"2026-08-10T21:10:49.452719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.819836Z","title":"Dense attention pyramid networks for multi-scale ship detection in sar images,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.819836Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:54503f5027e1acf5952589f70a96ad6fc2f8e1fc8b02edff62fcc146f8735aeb","observation_id":"6867cae4-617b-4914-ad0e-fbd3d9ae6b93","resolution":{"observed_at":"2026-08-10T21:10:48.819836Z","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":"2026-08-10T21:10:49.430293Z","title":"Cbam: Convolutional block attention module,","venue":null,"work_id":"7994db54-d844-4beb-bd5d-5146f05520b4","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.823644Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d2939cef17708725855ef72af330772091e28e34f0e0afa853ebc6f33d316ed1","observation_id":"8a806a5e-5eb8-4139-9b9d-2410ab76fb00","resolution":{"observed_at":"2026-08-10T21:10:49.434395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.417862Z","title":"A robust one-stage detector for multiscale ship detection with complex background in massive sar images,","venue":null,"work_id":"a19d2c66-744c-4dec-a28d-9bfca51c03c5","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.827587Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:351f8863ab91bec2a1c383428699274a6e7d5eb4acff982e17029b7dc25dda33","observation_id":"c5776d9e-78ef-4433-ad7e-fd282190f067","resolution":{"observed_at":"2026-08-10T21:10:49.422211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.396904Z","title":"Banet: A balance attention network for anchor-free ship detection in sar images,","venue":null,"work_id":"036cd8bf-8fb5-4696-b6f3-bc3e36e17708","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.831400Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:520a9eadb971210f5e8f9d9f7e31cbe6f67ea1479e855ada467aae1d142e863b","observation_id":"78a60491-0388-461e-8dcc-250fbb8980ba","resolution":{"observed_at":"2026-08-10T21:10:49.401652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.384488Z","title":"Multi scale ship detection based on attention and weighted fusion model for high resolution sar images,","venue":null,"work_id":"6f4e7c74-cf9e-4bda-b6e8-17ead4e4c9f0","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.834904Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:3d7d52706336a1bd1703b453ad2d6dc572a4b2b7f7073c5740c4925fa5e72242","observation_id":"5b94d8be-b573-45c5-93f3-a4b56c5fbcbe","resolution":{"observed_at":"2026-08-10T21:10:49.388814Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.371276Z","title":"Coordinate attention for efficient mobile network design,","venue":null,"work_id":"b0495e54-633d-4e8e-844d-9a1708351964","year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.839107Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:1e4b5368b83df7297835a743a01d17151b45b3906c7685f97181094bebdb524f","observation_id":"da87627e-b88b-43aa-8cef-3aa566529e5f","resolution":{"observed_at":"2026-08-10T21:10:49.375477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.359803Z","title":"Ppa-net: Pyramid pooling attention network for multi-scale ship detection in sar images,","venue":null,"work_id":"7edaf9a3-4444-4993-95f1-c72b3d18a3f8","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.842723Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:1b90e667c6fea2166587d2e44a5f0f68a09626665d3b2c18b9bc63a6885f7ce8","observation_id":"fa956744-3aa3-4d42-a109-db151edd8e94","resolution":{"observed_at":"2026-08-10T21:10:49.363973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.847402Z","title":"Imagpose: A unified conditional framework for pose-guided person generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.847402Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:f178a12110293b7f54068efbc0ceb78884e02228ad24276097232e267c918e87","observation_id":"456125ec-f911-40d8-81c1-0df0d61289f5","resolution":{"observed_at":"2026-08-10T21:10:48.847402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12705","last_updated":"2024-08-06T13:06:26Z","snapshot_observed_at":"2026-08-20T15:13:35.372038Z","submitted_at":"2024-07-17T16:26:30Z","title":"IMAGDressing-v1: Customizable Virtual Dressing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12705","snapshot_observed_at":"2026-08-10T21:10:48.851619Z","title":"Imagdressing-v1: Customizable virtual dressing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.851619Z"},"links":{"cited_paper":"/paper/2407.12705","citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:55b92852246e354bfd251bb49b80f9fc779f844232cc6d739bec5005c1e0ea90","observation_id":"673990fe-71ce-47dd-a2f0-1ac06e2ab9b2","resolution":{"observed_at":"2026-08-10T21:10:48.851619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.02482","last_updated":"2024-07-03T18:17:01Z","snapshot_observed_at":"2026-08-16T13:37:39.265753Z","submitted_at":"2024-07-02T17:58:07Z","title":"Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.02482","snapshot_observed_at":"2026-08-10T21:10:48.856077Z","title":"Boosting consistency in story visualization with rich-contextual condi- tional diffusion models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.856077Z"},"links":{"cited_paper":"/paper/2407.02482","citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:b08249c7d0161094c9a1af37d61f4252e3581c261d4a6cacf13496150212c73a","observation_id":"32b855da-7a82-41b8-ad83-3729d9667550","resolution":{"observed_at":"2026-08-10T21:10:48.856077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06313","last_updated":"2024-11-21T12:06:59Z","snapshot_observed_at":"2026-08-18T16:41:22.025938Z","submitted_at":"2023-10-10T05:13:17Z","title":"Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06313","snapshot_observed_at":"2026-08-10T21:10:48.860254Z","title":"Advancing pose-guided image synthesis with progressive conditional diffusion models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.860254Z"},"links":{"cited_paper":"/paper/2310.06313","citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:c9b600a5211eb12ac7db7513d2c2d0864d9e0d7e59f1b478904ccf47a22d4caa","observation_id":"11d8f04c-c8d2-4b4c-be15-c8af8c1c3674","resolution":{"observed_at":"2026-08-10T21:10:48.860254Z","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":"2026-08-10T21:10:49.334900Z","title":"Non-local neural net- works,","venue":null,"work_id":"d932d5c6-8015-4c03-bdf9-8eff39967bc7","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.864032Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:6d0e6931d5e921ddd23a00e02329150c0616c00a48566e30c8e094dec445b7b5","observation_id":"88ff9593-10fc-4503-84ba-61d912a399d5","resolution":{"observed_at":"2026-08-10T21:10:49.340238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.323087Z","title":"Gcnet: Non-local networks meet squeeze-excitation networks and beyond,","venue":null,"work_id":"44ebff09-a07d-4f9f-b02d-6b965fc6ff77","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.867824Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:ad481b1cb3bcb35d748c7ae8c72ef816739634646456a21d560e4e77d8c32c35","observation_id":"df243609-bdea-4855-a03f-642f4022a228","resolution":{"observed_at":"2026-08-10T21:10:49.326785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.311059Z","title":"Dual attention network for scene segmentation,","venue":null,"work_id":"f1481ea5-778b-4a5c-8d0e-a119ce5c2cda","year":2018},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.871484Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:6e124a5b379f3a7750aa4f35b026fd0afa54efeb8c00d2bf5b779453c52728f3","observation_id":"6cb6e9d2-c9ca-43af-adfe-35dd0da10008","resolution":{"observed_at":"2026-08-10T21:10:49.315873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.299006Z","title":"Ccnet: Criss-cross attention for semantic segmentation,","venue":null,"work_id":"efb296ad-d656-416e-85a9-3bf53537c528","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.875410Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:154dfa81e84a5cfb87e43c037fd289b0759c7dd240ee901dce3a10d62683aa9c","observation_id":"15ad21e9-8aed-47fb-b697-9d74043d5718","resolution":{"observed_at":"2026-08-10T21:10:49.303512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.286925Z","title":"Squeeze and excitation rank faster r-cnn for ship detection in sar images,","venue":null,"work_id":"0a9d06c5-7322-4fc2-bfa7-224b398aa453","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.878924Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:2ebf3804373b96daa820975f0ed4bf4722d1f32e0b07ebbc24933b8e424b35e1","observation_id":"cea8007f-d844-4b9f-8a59-8c5fbb230138","resolution":{"observed_at":"2026-08-10T21:10:49.291434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.882313Z","title":"Dynamic r-cnn: Towards high quality object detection via dynamic training","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.882313Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:1e355cd9ebe6bab3a86e328d3d84f6416685469fb01f780fd120cfb3f36b4fbc","observation_id":"66cf86d4-0edc-46e3-b190-91d4debdc827","resolution":{"observed_at":"2026-08-10T21:10:48.882313Z","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":"2026-08-10T21:10:49.270580Z","title":"Rethinking classification and localization for object detection,","venue":null,"work_id":"797f6111-9ffe-4d04-98d6-d88cefebcb88","year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.886044Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:3634a2b26bc7e0a0287b9a9f30a5cdb5d46d6a70e87bc0489847b264a6040f64","observation_id":"e9280b19-932d-4fcf-aa70-18cfabe274fa","resolution":{"observed_at":"2026-08-10T21:10:49.277818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.258574Z","title":"A cascade rotated anchor-aided detector for ship detection in remote sensing images,","venue":null,"work_id":"69436583-d4e9-427e-b24e-4459a2a87275","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.890301Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d5533980dc5a2cdcaf152134fcdc60e7f0829da386f61c3ada1c10e2427f16c8","observation_id":"e5e8cc99-c1c8-485f-8d06-f8a8e881a055","resolution":{"observed_at":"2026-08-10T21:10:49.262743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.245606Z","title":"Fcos: Fully convolutional one- stage object detection,","venue":null,"work_id":"d11de09b-88f1-4998-a4f5-385de85f4384","year":2019},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.894068Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:a48f3f70917b26be87abfe3b80361472231b8533220e7c12dd9078500705429c","observation_id":"90a8381b-3ec3-4dcc-aafb-66034692766d","resolution":{"observed_at":"2026-08-10T21:10:49.250621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.232520Z","title":"Learning to match anchors for visual object detection,","venue":null,"work_id":"758ede03-a742-47b7-bf3a-903e64ccca06","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.897761Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:ee5808398e7ff5f65c42572c5a8790e3f0b8e1c24abedfeb0110c056b4c8c125","observation_id":"ab8b660b-e8a4-428d-9dfa-81de3d46f646","resolution":{"observed_at":"2026-08-10T21:10:49.236954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.214742Z","title":"Frequency- adaptive learning for sar ship detection in clutter scenes,","venue":null,"work_id":"05d659b0-c60a-4c54-9ea3-71727bb656b1","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.901472Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:a7566fed3329f7cbfe3004453d2f936a63dfb0fe3ad76f4f9a8332619e14d49b","observation_id":"0573b94f-a2e4-4010-a175-588862395aec","resolution":{"observed_at":"2026-08-10T21:10:49.219674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:48.905100Z","title":"Yolov8: A novel object detection algorithm with enhanced performance and robustness,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.905100Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:dbb45bdd0e83b33e4aa91ed576bb273d4d82f017684c4cd8ac51de1ee8f587cf","observation_id":"d8c84053-2301-41dc-b445-4574152fd753","resolution":{"observed_at":"2026-08-10T21:10:48.905100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08430","last_updated":"2021-08-06T03:22:14Z","snapshot_observed_at":"2026-08-19T15:19:25.831687Z","submitted_at":"2021-07-18T12:55:11Z","title":"YOLOX: Exceeding YOLO Series in 2021","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.08430","snapshot_observed_at":"2026-08-10T21:10:48.909668Z","title":"Yolox: Exceeding yolo series in 2021,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.909668Z"},"links":{"cited_paper":"/paper/2107.08430","citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:dacd9a6c78d954f0f0434c8f79eb8d32128e3244f99304d015c516af26e948e6","observation_id":"6be40b7a-877d-4032-bb90-a5171bb70b87","resolution":{"observed_at":"2026-08-10T21:10:48.909668Z","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":"2026-08-10T21:10:49.161254Z","title":"A sidelobe-aware small ship detection network for synthetic aperture radar imagery,","venue":null,"work_id":"a0d2e750-b07b-4e74-a8ff-d38243f2da26","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.914202Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d07644fa9cfd6b7a44aeb3484a13cca943a044039be050b50758b191c373bf32","observation_id":"be6f2af8-5de4-4611-95d0-675c2cdfc847","resolution":{"observed_at":"2026-08-10T21:10:49.165165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.149858Z","title":"Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors,","venue":null,"work_id":"da8b460b-1bde-445c-8c2f-f542a43d3636","year":2023},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.917725Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:5dd0b61e80cf67dcf519da2108c6b2893fb502fa3bd52b09b669e9eaa9234681","observation_id":"c17e44df-7276-4c61-b553-c94ba6dfe927","resolution":{"observed_at":"2026-08-10T21:10:49.154019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.137122Z","title":"Atsd: Anchor-free two-stage ship detection based on feature enhancement in sar images,","venue":null,"work_id":"47df0cde-8bef-400b-97e8-7d411c051e3c","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.921852Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:31c9031d8d6617ed5ce87bdd0adae584b733aade142445247a73caab35bb2391","observation_id":"a9f2f4c7-b819-4ba8-b897-6336b6d43fa1","resolution":{"observed_at":"2026-08-10T21:10:49.141902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.125715Z","title":"Dbw-yolo: A high-precision sar ship detection method for complex environments,","venue":null,"work_id":"61afa49f-6b27-4d99-b68b-b7a457de3413","year":2024},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.924995Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:a2b8dd340ebf50392a99149b06e2d716de685adbe098dccc71bddbe6ab154c84","observation_id":"55874331-5036-4a26-a6ff-ba7d856bfd67","resolution":{"observed_at":"2026-08-10T21:10:49.129752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.113163Z","title":"A rotational libra r-cnn method for ship detection,","venue":null,"work_id":"55fe33ff-c176-458c-a4f8-553690dc3097","year":2020},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.928505Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:45abf555714ed78a5c3f7ddf40967ccf5fec57455f3241a10b745386c528ceef","observation_id":"88df208a-69b7-49e9-9636-935819d8bb5b","resolution":{"observed_at":"2026-08-10T21:10:49.117696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.098260Z","title":"Deformable convolutional networks,","venue":null,"work_id":"9f5fb1b1-dc6d-4b6b-93d1-42f1c5235bfb","year":2017},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.932807Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d0c9bc75f826f754c83fafe27cedbe941d8b31c5a0dbb5a9eccd64015ca75697","observation_id":"d83f3438-4e9a-4c5c-ad16-5000efc74291","resolution":{"observed_at":"2026-08-10T21:10:49.102627Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.084750Z","title":"Msif: Multisize inference fusion-based false alarm elimination for ship detection in large-scale sar images,","venue":null,"work_id":"6830a57e-72fb-4f51-a357-d9de9cf700ee","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.936491Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:d8e923f4a9ba47298df21f42188eec260cfc8cf51fbfa51a332f1282ce4a0afb","observation_id":"f16ebd42-d44c-4819-808c-89708ec3bbca","resolution":{"observed_at":"2026-08-10T21:10:49.089869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.063956Z","title":"Lemon-yolo: an efficient object detection method for lemons in the natural environment,","venue":null,"work_id":"5378e035-c7c4-4a89-8ffc-dc443eb69e3c","year":1998},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.940136Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:4fc4c746ac547d931a203d5a4549be6bde7f042c0bb5f67a14af227b6f409dfe","observation_id":"d4be33db-336b-45eb-8f68-4a64602fc855","resolution":{"observed_at":"2026-08-10T21:10:49.068350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.050581Z","title":"Sii-net: Spatial information integration network for small target detection in sar images,","venue":null,"work_id":"0958da7c-ec61-40bc-b05c-f9262b0ebaa9","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.944409Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:277533b6a7290877314035f296a4477b3bb58630bebc6032ca32d50fb5d0dc01","observation_id":"5c6930bc-058e-447c-8291-0491b662340a","resolution":{"observed_at":"2026-08-10T21:10:49.055153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+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":"2026-08-10T21:10:49.033273Z","title":"A high-effective implementation of ship detector for sar images,","venue":null,"work_id":"01fde6cd-cb01-4985-a159-e001670390c8","year":2022},"citing_paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-10T21:10:48.947999Z"},"links":{"citing_paper":"/paper/2501.06053"},"observation_digest":"sha256:5628738d30c5322816c4aadaf8998e3c5d78ad86faa98a14f7e73979db2d54e6","observation_id":"e0246c4f-27d2-418a-8ec8-c1a93ac88979","resolution":{"observed_at":"2026-08-10T21:10:49.039980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.06053","last_updated":"2025-01-10T15:33:37Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T16:42:11.784308Z","submitted_at":"2025-01-10T15:33:37Z","title":"Enhancing, Refining, and Fusing: Towards Robust Multi-Scale and Dense Ship Detection"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":58},"total_outbound_references":68},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2501.06053."}