{"as_of":"2026-08-23T17:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c20f4865f90b5b6623940c3dca26f34c2f473f5f711cee3233f02a7971b1c6d2","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:10:13.262863Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:10:13.152392Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T14:10:13.314206Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"cited_work":{"arxiv_id":"1908.03692","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.03692","snapshot_observed_at":"2026-08-14T14:10:13.314206Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","venue":"cs.CV","work_id":"5b7219e0-1144-4085-ae03-a3902701975c","year":2019},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.152392Z"},"links":{"cited_paper":"/paper/1908.03692","citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:c90624c4a502a7a0384468a9b851d1bf26a582b4b1399fc0e91748dc577102a4","observation_id":"96acb3ad-c620-45f8-a7f2-ed070f3d00de","resolution":{"observed_at":"2026-08-14T14:10:13.321537Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.03692/citation-record","integrity":"/paper/1908.03692/integrity","json":"/paper/1908.03692/citation-record.json","paper":"/paper/1908.03692"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"cited_work":{"arxiv_id":"1908.03692","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.03692","snapshot_observed_at":"2026-08-14T14:10:13.314206Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","venue":"cs.CV","work_id":"5b7219e0-1144-4085-ae03-a3902701975c","year":2019},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.152392Z"},"links":{"cited_paper":"/paper/1908.03692","citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:c90624c4a502a7a0384468a9b851d1bf26a582b4b1399fc0e91748dc577102a4","observation_id":"96acb3ad-c620-45f8-a7f2-ed070f3d00de","resolution":{"observed_at":"2026-08-14T14:10:13.321537Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.638585Z","title":"CvxEDA Algorithm We focus on processing large scale EDA data","venue":null,"work_id":"2ca6c8d0-77b7-471f-83a0-519931b6a709","year":null},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.157898Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:8e198c19079b827f5cc053ca3423e023d4d5442a316ffb40f7d8d580a08cacbf","observation_id":"20a66f0c-d5c1-4328-9607-04ce07c4a400","resolution":{"observed_at":"2026-08-14T14:10:13.643130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.624394Z","title":"The re- sults and analysis can validate our idea and explain why our method achieves remarkable performance in large scale data","venue":null,"work_id":"1c0660df-ec6f-4c2f-b961-e079dafc0bbd","year":1940},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.162712Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:99cb9ba9c4c4df044bc10ae75f1e6fcd6bf84cd5970fbaf23c08aefff3065081","observation_id":"05106256-4a60-4fc7-8274-95bec7a184f3","resolution":{"observed_at":"2026-08-14T14:10:13.629006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.610298Z","title":"For the specific significance of research, we convert emotion recognition to a binary classification","venue":null,"work_id":"44a00234-4db0-4717-b7c9-76cce3e9b03d","year":null},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.167588Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:81b263e053087a07f963bb414497ef62c0a7d37e5bfb204d0e0a338406d438e5","observation_id":"67def25f-6c60-4b32-849d-2905f0126caa","resolution":{"observed_at":"2026-08-14T14:10:13.615074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.596269Z","title":"Quantifying driver stress: Developing a system for col- lecting and processing bio-metric signals in natural sit- uations,","venue":null,"work_id":"f5bb7607-4cec-4b07-8613-7cf8c9114f80","year":1999},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.172436Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:9f622513a1bc57d46e701febf6b31be8d56d81182765fe81f0511d255bda0c89","observation_id":"9e1880e7-9c29-464d-b877-64e1d7f05c58","resolution":{"observed_at":"2026-08-14T14:10:13.601107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.582768Z","title":"Pervasive and unobtrusive emotion sensing for human mental health,","venue":null,"work_id":"c3a4f2f9-888d-43f2-a505-240ae0243f91","year":2013},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.177231Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:53c8477fede7c8172910cd6900a72d9d7edc4679379cac45ee8ca739de2119bd","observation_id":"3c62ba80-ff09-4eb4-962b-257a96a8ac57","resolution":{"observed_at":"2026-08-14T14:10:13.587214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.569225Z","title":"Classification of emotional signals from the deap dataset,","venue":null,"work_id":"94c2c76b-e0c6-40fd-88ad-5e898ee3b10e","year":2016},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.181188Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:4ee0bb6647da1c25aeaf0571b06c1aca201833e10b04654a4c1826cbae501964","observation_id":"5cf6059e-1084-4bdf-8856-401feaf1a384","resolution":{"observed_at":"2026-08-14T14:10:13.573812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.555542Z","title":"Arousal and valence recog- nition of affective sounds based on electrodermal activ- ity,","venue":null,"work_id":"3dc5c68e-b3da-479c-8c35-e63eb9faab7f","year":2017},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.185000Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:c13b2a303975c07bf86dbc287f7de1c2c620719f331bd48a40a46b42fdcc038d","observation_id":"4aabfa8e-281f-46ee-bbff-0b781c339024","resolution":{"observed_at":"2026-08-14T14:10:13.560368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.542151Z","title":"Emo- tion recognition based on the multiple physiological sig- nals,","venue":null,"work_id":"98608abe-01e9-4dcf-8cea-ca15809b71d1","year":2016},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.189499Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:eab4b79f0463c6d459004b77d7ed454db98f669aaa080b02c353fd580e013369","observation_id":"3485092e-2c44-4aec-b95f-b22111120ec1","resolution":{"observed_at":"2026-08-14T14:10:13.546566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.528244Z","title":"Eeg-based emotion classification using deep belief networks,","venue":null,"work_id":"4e55be66-25d9-4802-b144-6cf36533f785","year":2014},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.193481Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:936d5192658d58d923b4770374f50fd190ee9d127c20b3dd23a9a4cca89cbece","observation_id":"1c61a42b-955c-4346-80f4-16b59d40c5e5","resolution":{"observed_at":"2026-08-14T14:10:13.532908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06448","last_updated":"2016-02-29T21:33:45Z","snapshot_observed_at":"2026-08-14T22:22:07.158760Z","submitted_at":"2015-11-19T23:29:55Z","title":"Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06448","snapshot_observed_at":"2026-08-14T14:10:13.197726Z","title":"Learning representations from eeg with deep recurrent-convolutional neural networks,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.197726Z"},"links":{"cited_paper":"/paper/1511.06448","citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:4380ae47825fce61d25d024963e2a1d45cba0e2d9b69b62f3a6a190a9a33bcb6","observation_id":"ecc2a540-1d02-47ce-b310-0d5a1e0de279","resolution":{"observed_at":"2026-08-14T14:10:13.197726Z","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":"2026-08-14T14:10:13.514201Z","title":"Deap: A database for emotion analysis; using physiological signals,","venue":null,"work_id":"e562b845-e69d-415b-abd8-b52480c5f5d7","year":2012},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.202108Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:8665a7c7c7248e922bad91e62f691f45eef42cc00a4ef764fc6575c1b1bbd991","observation_id":"dc8820b9-a5a4-4b50-bb7d-79326775dc6c","resolution":{"observed_at":"2026-08-14T14:10:13.518873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.501279Z","title":"http://bcmi.sjtu.edu.cn/ seed/,","venue":null,"work_id":"126a717d-77a1-4003-9a98-a25a78d7886a","year":null},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.206563Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:0f8dfdae1419fa3c9db7461bcf00c83d2bca8013d48376dfd579d65369506298","observation_id":"ed770c32-b853-422c-af45-09fb10706a13","resolution":{"observed_at":"2026-08-14T14:10:13.505355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.487803Z","title":"A multimodal database for affect recognition and implicit tagging,","venue":null,"work_id":"3cfd6d8c-fe7b-412e-af52-2a667e62b8de","year":2012},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.211961Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:37987c1cf4f42d2430d00f60d5a7709aa579fbaed02f1b9f2257fe5353b8273c","observation_id":"8dab4c3a-141e-4f07-8f56-43128a1c175a","resolution":{"observed_at":"2026-08-14T14:10:13.492306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.474570Z","title":null,"venue":null,"work_id":"e96d3ee8-ab84-4a3c-b620-12dd6cd71f5c","year":2011},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.216346Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:59c40c8aba282ccaf8674fdd5d600ae573cd5cd5f5375ec59f047c3c13e139d7","observation_id":"3049237e-4284-45a8-b790-96363c3c015e","resolution":{"observed_at":"2026-08-14T14:10:13.478985Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.460654Z","title":"Affective video con- tent representation and modeling,","venue":null,"work_id":"99557e20-9f16-486d-87a5-d3f97f9c0b33","year":2005},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.220626Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:c81e48d3492d5f5ec3c6f15c7ce4451980c7877ef6e7435ffdb4a5aaecc5bf0f","observation_id":"acf1b60a-9dca-4735-8272-464c33077787","resolution":{"observed_at":"2026-08-14T14:10:13.465245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.446555Z","title":"The pmemo dataset for music emo- tion recognition,","venue":null,"work_id":"e619bce2-fb5f-4716-b3f2-dc6e6854a2ac","year":2018},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.225159Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:7d9e1e7464bde31daceb23fa476315beb04cd53f07b4cc7cf6a87f6f8b59d7bb","observation_id":"943dd351-b632-4819-b044-29d4f24e57ce","resolution":{"observed_at":"2026-08-14T14:10:13.451449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.430897Z","title":"Cross-subject eeg feature selection for emotion recognition using transfer recursive feature elimination,","venue":null,"work_id":"0c85ee7a-e203-41c6-a7f3-0e012ce7a637","year":2017},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.229520Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:5b217fffb2fa84875b03b090715f1911fd883e9778d014467f1fdac1afc958a7","observation_id":"c1a22dcf-77de-40ca-abf5-451e9292eaaa","resolution":{"observed_at":"2026-08-14T14:10:13.436834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.415617Z","title":"The circumplex model of affect: An integra- tive approach to affective neuroscience, cognitive devel- opment, and psychopathology,","venue":null,"work_id":"7d1d0895-d217-4798-bc5b-3009318be667","year":2005},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.233794Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:ba9f3c3a798b6baedb82ad9bf929bab461ef91abc57fd1c723044435e50bbc3d","observation_id":"070c1bab-d302-4ec2-9d06-49655c66f1b4","resolution":{"observed_at":"2026-08-14T14:10:13.420219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.400685Z","title":"Deep learning and its applica- tions to signal and information processing [exploratory dsp],","venue":null,"work_id":"ac862cec-b139-45e2-87a6-d2ee34d18657","year":2011},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.239407Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:9cb236157ff3e4585fdf3cd3743a46dd272cf02a55ef7600405a9adb264cf7cb","observation_id":"679f4fbf-2bbf-4443-bd89-eb06cdfa1d53","resolution":{"observed_at":"2026-08-14T14:10:13.405333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.385761Z","title":"cvxeda: A convex optimization approach to electrodermal activity processing,","venue":null,"work_id":"6cffd0eb-ce4b-4aa6-b89b-cf922ec3412f","year":2016},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.243754Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:909d388ddac415ee7a825841cda4217eeaab4c04ab5a638070a78d1d796a5add","observation_id":"b8e159a0-e324-44f8-82a1-e297160aa2f3","resolution":{"observed_at":"2026-08-14T14:10:13.390574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.369992Z","title":null,"venue":null,"work_id":"e4ab398c-dfa9-408b-a81b-af318a2a8532","year":2012},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.248909Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:9939f9f048e557d99f6308c874913fc8358583229290d2fb7389f1637dc51c91","observation_id":"c93874c1-42a5-419f-b09f-efb2d6e56158","resolution":{"observed_at":"2026-08-14T14:10:13.375068Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.354829Z","title":"Developing a benchmark for emotional analysis of music,","venue":null,"work_id":"1c4bb260-6f58-479a-a013-21851052bb56","year":2017},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.253204Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:c676eb87a386e284cb2b3efd7e3d6b7eaeb6868fc502e913384a2ba4af0d2f9a","observation_id":"7f764dd4-1f22-402d-92f0-af886ec0200a","resolution":{"observed_at":"2026-08-14T14:10:13.359884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-14T14:10:13.258508Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.258508Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:beecef3d6610e1b8dc0919f823550eb2f5cb55e1853dfdcf91f1ec20a1bfa224","observation_id":"cc9ef9f8-f8d7-4d67-959b-02a24d5aba0f","resolution":{"observed_at":"2026-08-14T14:10:13.258508Z","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":"2026-08-14T14:10:13.331834Z","title":"Emotion recogni- tion based on physiological changes in music listening,","venue":null,"work_id":"5a4876af-35e1-4ca7-bc84-6650815ad5cb","year":2008},"citing_paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:10:13.262863Z"},"links":{"citing_paper":"/paper/1908.03692"},"observation_digest":"sha256:2466c127b960a5d613d7d30d9ed528e50f5fcce78751d125d9a266838d23a17a","observation_id":"318d01b0-a31b-4af0-b559-625235962b34","resolution":{"observed_at":"2026-08-14T14:10:13.336351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.03692","last_updated":"2020-08-03T01:28:18Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-18T23:36:33.707687Z","submitted_at":"2019-08-10T05:18:21Z","title":"User independent Emotion Recognition with Residual Signal-Image Network"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":1,"verified_fuzzy":20},"total_outbound_references":25},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:1908.03692."}