{"as_of":"2026-08-08T18:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:50d57dea08f0827a7a6cb3fc44b5a3577216381479a6a8de7b6bed85be5b9936","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:33:06.955163Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2507.02510/citation-record","integrity":"/paper/2507.02510/integrity","json":"/paper/2507.02510/citation-record.json","paper":"/paper/2507.02510"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:08.468207Z","title":"Brain computer interfaces, a review,","venue":null,"work_id":"12413a6f-64bb-4cc8-af0d-0bbdf212a9bb","year":null},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.788779Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:6626c537717b0991c5dbf6d91d231e19bb535ca72b4e600f89dc9ca6bf6be504","observation_id":"03c92b56-898b-4f20-a1cc-81813d9de914","resolution":{"observed_at":"2026-08-06T20:33:08.476122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.797658Z","title":"Brain – Computer Interface Spellers: A Review,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.797658Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:117c8b228b7195417bb9ed44599116a792211859a7403d319f5f7db7f2735dff","observation_id":"fee792fd-cce8-4e7c-9ae9-dbd281eb0ad1","resolution":{"observed_at":"2026-08-06T20:33:06.797658Z","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":"10.1088/1741-2552/abecc5","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.244321Z","title":"Combining generative adversarial networks and multi-output CNN for motor imagery classification,","venue":null,"work_id":"b9142f31-0252-445a-9b51-5a38e818da02","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.801958Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:34812840b858fba9454db4bd9cf1fb6a9416f1e4b5103ff92af15a14aaa99067","observation_id":"07894d8f-4c0e-42e6-98f6-dd2fc433744c","resolution":{"observed_at":"2026-08-06T20:33:07.251125Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.806131Z","title":"Autoreject: Automated artifact rejection for MEG and EEG data,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.806131Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:ad0f748cc17eb7cb7eac6f7392174b21cd082ec38ec921e1906050ce69c6e078","observation_id":"92bfd6bb-d731-4bc1-8dd3-2b703e27716e","resolution":{"observed_at":"2026-08-06T20:33:06.806131Z","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":"10.1186/s12984-023-01169-w/tables/5","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.220877Z","title":"Generative adversarial networks in EEG analysis: an overview,","venue":null,"work_id":"67883d4a-a3d4-43be-a5f9-37a27176a960","year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.810121Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:dcee1b0eb6d4f8fe0d1776370c3f93f03bf3972282bac2ece8cb1295e32d68c3","observation_id":"76bdbeaf-92d5-4843-aa4a-af002f08df03","resolution":{"observed_at":"2026-08-06T20:33:07.225139Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.814338Z","title":"An Ensemble CNN for Subject-Independent Classification of Motor Imagery-based EEG,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.814338Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:b17cc8529f18d9455b99f980a6efc21e662735ecc80260a8dcd48eb9cf41e032","observation_id":"fc2af354-72de-4fe8-b67d-98d09351e266","resolution":{"observed_at":"2026-08-06T20:33:06.814338Z","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":"10.1016/j.bspc.2018.12.027","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.206146Z","title":"Separated channel convolutional neural network to realize the training free motor imagery BCI systems,","venue":null,"work_id":"9c6a1229-8a86-4697-80c2-d075cddb4bda","year":2019},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.818293Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:54caee380a5758cae5ffe71ad11e82170b9fa1ce02f9d03da486528a8b02986e","observation_id":"ab33898d-3c8f-4498-9fbe-0b5ebfb64793","resolution":{"observed_at":"2026-08-06T20:33:07.210529Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-030-22885-9_12/figures/7","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.192460Z","title":"Cross-Subject EEG Signal Classification with Deep Neural Networks Applied to Motor Imagery,","venue":null,"work_id":"e6535e95-3ef1-4e99-93d6-a419c7006bdb","year":2019},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.822493Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:40c7cbe94f4232e83bca25dd4dae3cd568e97b8b8a310fa7b0cc89830e7edea3","observation_id":"9d17c6a8-fe44-4a4d-8ed7-a78e81a0c2de","resolution":{"observed_at":"2026-08-06T20:33:07.197063Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/computers9030072","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.178717Z","title":"Fusion Convolutional Neural Network for Cross-Subject EEG Motor Imagery Classification,","venue":null,"work_id":"c639890b-cb55-4f9f-9885-c64e9fdf8c47","year":2020},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.826257Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:936a15de5e94d8a258ca2cf0c5a2115bcda6aea6e4a1a1f2570fa289e9d3bf7d","observation_id":"04425bdb-fa1b-423c-866f-67acaba8bf33","resolution":{"observed_at":"2026-08-06T20:33:07.182909Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.00918","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:08.246577Z","title":"Deep Learning Based Inter - subject Continuous Decoding of Motor Imagery for Practical Brain -Computer Interfaces,","venue":null,"work_id":"a9c9adb9-48a7-4293-90e1-2e730556bbba","year":2020},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.829943Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:1dc8e1fd1570fa0a4ce969c7883af931cb12fb3d0c967c0b3b567e82fa030077","observation_id":"5a57059e-0758-4041-8930-266e515c4bbf","resolution":{"observed_at":"2026-08-06T20:33:08.253062Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.833819Z","title":"CNN -based Approaches For Cross -Subject Classification in Motor Imagery: From the state -of-the-art to dynamicnet,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.833819Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:c02999381e72147a6398194a9ff0ddae0251f97d3a0311f30927dd489136c6a8","observation_id":"b5d33c55-0b61-4f29-848c-3ece7ec2324f","resolution":{"observed_at":"2026-08-06T20:33:06.833819Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:06.837496Z","title":"Dual Attention Relation Network With Fine-Tuning for Few -Shot EEG Motor Imagery Classification,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.837496Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:04a677face24ea0c90f0ca35cd3aa1fd6d9b26ea0f48f86c9f0032004ae79c37","observation_id":"e662b962-1a03-4c92-89c0-8c579ec76401","resolution":{"observed_at":"2026-08-06T20:33:06.837496Z","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":"2022.10405","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.996356Z","title":"Excellent fine-tuning: From specific-subject classification to cross-task classification for motor imagery,","venue":null,"work_id":"31b14c29-4975-49c2-85e8-2a5db4cbc4f0","year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.841227Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:3b9fb664c40fdb34ff28632df3113855693f0b0ea2d557ea87f338bfe99ae1f8","observation_id":"f55c5cf8-1a9f-48b6-ac78-008522493f6b","resolution":{"observed_at":"2026-08-06T20:33:08.007786Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.844891Z","title":"A novel deep learning approach for classification of EEG motor imagery signals,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.844891Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:1e2000ba0cd8e07cad7022b37215b33e99e6b63cc7f3118324a7c9e6dc71db54","observation_id":"3e4ca940-12c3-4f3a-a67e-f1ea099aefe4","resolution":{"observed_at":"2026-08-06T20:33:06.844891Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/s20164485","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.155306Z","title":"Data augmentation for motor imagery signal classification based on a hybrid neural network,","venue":null,"work_id":"02efe1e0-efbb-4a0e-a1dc-30bab43cc151","year":2020},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.848708Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:90ad160e831c76f30c36ee5a17868673833e99b6e526bd66574444c8b2e4657f","observation_id":"13a0775c-6bea-41dd-b41c-5f751fe24418","resolution":{"observed_at":"2026-08-06T20:33:07.160188Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/app11041798","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.141545Z","title":"4 -class mi-eeg signal generation and recognition with cvae-gan,","venue":null,"work_id":"b3cc97f2-c4a5-4e8b-98ac-9f1dfc36d23b","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.852439Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:4d158ccc57caa34ef5ce3524ba9a0549addabd753fb5062f1b17c0adc9994fdb","observation_id":"54523373-96cb-47df-810f-38747837e8ef","resolution":{"observed_at":"2026-08-06T20:33:07.145945Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.856698Z","title":"Motor Imagery Classification Enhancement using Generative Adversarial Networks for EEG Spectrum Image Generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.856698Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:915d008369a8dff104bfe27a955a9ebd17d009d95139f0a5a970782010aceaa2","observation_id":"d959899b-f315-484a-a060-448b5c96f169","resolution":{"observed_at":"2026-08-06T20:33:06.856698Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:06.860984Z","title":"Toward calibration -free motor imagery brain –computer interfaces: a VGG -based convolutional neural network and WGAN approach,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.860984Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:77ee86d7ce58e23d01037137efacce7779a490db2dadb02f5f52679178c65336","observation_id":"00493f22-1998-489b-ba27-c6b15398d8a4","resolution":{"observed_at":"2026-08-06T20:33:06.860984Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s13534-021-00190-z/tables/8","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.115247Z","title":"CNN based classification of motor imaginary using variational mode decomposed EEG -spectrum image,","venue":null,"work_id":"b5835423-ab84-4fc0-9ec0-529b4ef257cb","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.865216Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:c24820f2f9aecdd6bac3f2840d4444676ef54ab57950dc5f7e3e7309f41fdae9","observation_id":"bf5e1981-0403-4246-8924-4855888b7013","resolution":{"observed_at":"2026-08-06T20:33:07.119581Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-030-92310-5_46/figures/5","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.101396Z","title":"EEG-Based Classification of Lower Limb Motor Imagery with STFT and CNN,","venue":null,"work_id":"4fa12f78-0356-43bc-981b-a19c58d02dca","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.869913Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:5ccbce1654391392c796a308c44e4717c8ca7149656c7b733785044bad67f47f","observation_id":"77dc3fef-77a4-4db1-99b4-f5c815e04c8e","resolution":{"observed_at":"2026-08-06T20:33:07.105792Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1140/epjs/s11734-022-00683-7","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.087584Z","title":"Short -time Fourier transform and embedding method for recurrence quantification analysis of EEG time series,","venue":null,"work_id":"590a24d1-7995-4a6e-957d-95b2ed43555c","year":2022},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.874056Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:88ebb0f80c69a1de5a74742e04ec0f7c92695b97dbd4add018ae04c14bb85c17","observation_id":"01a829a2-75ce-499c-a39a-bd351c007e5e","resolution":{"observed_at":"2026-08-06T20:33:07.092157Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"1984.11643","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.829741Z","title":"Signal Estimation from Modified Short -Time Fourier Transform,","venue":null,"work_id":"5bb31b95-c131-44f0-a04e-58ff089b2782","year":1984},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.877838Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:ee863bbf65ed0af2ba82831eac4a8f9006ead47fcc27512d2b819560e4ab157c","observation_id":"7bf02423-5607-4bfa-993a-bd0d84626872","resolution":{"observed_at":"2026-08-06T20:33:07.839128Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:08.443763Z","title":"BCI Competition IV","venue":null,"work_id":"b630f521-47a9-4744-9bd0-87a05f86f0ea","year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.881504Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:1162a4e61138041f2604a21a705c4c37ea2f024d09d534068122a68f97022f45","observation_id":"5be81849-d99f-4923-90b8-4424c8d5cf42","resolution":{"observed_at":"2026-08-06T20:33:08.453431Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.885464Z","title":"Wavelet Transform Time-Frequency Image and Convolutional Network- Based Motor Imagery EEG Classification,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.885464Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:8f87125af7745b6ea36b2a30ac3bdee714e4012268b951ca3bbfb83c34f3e03c","observation_id":"86ab7ea0-035a-4712-b1b8-e15f149ec8fc","resolution":{"observed_at":"2026-08-06T20:33:06.885464Z","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":"2026-08-06T20:33:08.416414Z","title":"BCI Competition 2008-Graz data set A Experimental paradigm,","venue":null,"work_id":"de0a080b-cf04-43cc-833f-1537dafad2dd","year":2008},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.889500Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:e69ebcdf43ec47e2743181d30b9d2093fbc97c9036968e8abab1c2760e3a29b2","observation_id":"c18da23d-132f-4dc1-a543-802080637939","resolution":{"observed_at":"2026-08-06T20:33:08.429393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:08.389275Z","title":"‘BCI competition 2008 –Graz data set B’ ,","venue":null,"work_id":"bdbb0549-933f-4f60-be8c-fe36041ff06e","year":2008},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.893046Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:197d09339ba7d2cde9697bbf6900c84a950e24ada186e73b9b21c874f8a76d55","observation_id":"18326323-2338-440d-8403-10f3f249cf86","resolution":{"observed_at":"2026-08-06T20:33:08.401958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1111/psyp.14320","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.074595Z","title":"Validation of the g.tec Unicorn Hybrid Black wireless EEG system,","venue":null,"work_id":"a2c059b4-5559-4e78-949f-4c0ff2995447","year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.897351Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:86b28b3b9066f52549315516f4c9879ceb3c5fd7e2298314911edd077ce18f0d","observation_id":"c07f6b38-a87d-477c-a75f-4b8e914f4dba","resolution":{"observed_at":"2026-08-06T20:33:07.078886Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/78.678493","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.061119Z","title":"Generalized digital butterworth filter design,","venue":null,"work_id":"668811ba-2666-4ebb-be70-17eb9e51c81c","year":1998},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.901728Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:cc4dfc8b3ac1acc69e114da6f194a0e24f6367b03fdda11f0ca085b46212d15c","observation_id":"efe4c113-b2de-4b28-85ab-af7dcef3cc3e","resolution":{"observed_at":"2026-08-06T20:33:07.065497Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.905635Z","title":"A compact multi -branch 1D convolutional neural network for EEG-based motor imagery classification,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.905635Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:6ef3ddb8a5f297c3be56620e734be598d1b0cfc9618bee299ae13895fa9da38e","observation_id":"989cd1af-589a-4368-94cb-7c45cc5b2078","resolution":{"observed_at":"2026-08-06T20:33:06.905635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-07-06T03:53:32.549552Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-06T20:33:06.909432Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.909432Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:2c0bd4f2d2500a0aac0616fdb74e025af431002d39ee7fff3b2c5e2fe993582b","observation_id":"99b46321-1db1-4d48-b631-3a2ef5d9c96c","resolution":{"observed_at":"2026-08-06T20:33:06.909432Z","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":"2026-08-06T20:33:08.350501Z","title":"P-TELU: Parametric Tan Hyperbolic Linear Unit Activation for Deep Neural Networks,","venue":null,"work_id":"052b3b8a-5c5e-461a-ac4e-0a235ee3cabc","year":2017},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.913553Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:6c27660506e72fad0ff9548bb28137cc23b26393183d344a9a8acfdfa8fe8c42","observation_id":"c7588d4f-4e05-4583-8c6d-bc425076db4c","resolution":{"observed_at":"2026-08-06T20:33:08.367418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.917118Z","title":"Improving the efficiency of RMSProp optimizer by utilizing Nestrove in deep learning,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.917118Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:f2dd4ae475a24e31049ce2a3eb490d4449012cdaa36b26f77dda85f8479b6b44","observation_id":"3df89d62-7bb2-494a-b485-81ce47204644","resolution":{"observed_at":"2026-08-06T20:33:06.917118Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07288","last_updated":"2023-06-20T00:48:23Z","snapshot_observed_at":"2026-08-04T08:19:07.006896Z","submitted_at":"2023-04-14T17:58:23Z","title":"Cross-Entropy Loss Functions: Theoretical Analysis and Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07288","snapshot_observed_at":"2026-08-06T20:33:06.921152Z","title":"Cross -Entropy Loss Functions: Theoretical Analysis and Applications,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.921152Z"},"links":{"cited_paper":"/paper/2304.07288","citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:752033b55b4ec60ca30efaeb7fde5274a9e768c368fc5f8dbe4d946307a89ea9","observation_id":"26f2e18f-9047-486e-85b4-867eb85afcb6","resolution":{"observed_at":"2026-08-06T20:33:06.921152Z","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":"2026-08-06T20:33:08.333713Z","title":"Understanding and Improving Early Stopping for Learning with Noisy Labels,","venue":null,"work_id":"e940fc68-1411-432f-93ed-9bb144eb8618","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.924989Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:addded2716ee05685aa8f7fdce62a79d70a99a295208ba23795580e2efb8b654","observation_id":"5110ce9f-7a93-4979-ace1-e87de83c7611","resolution":{"observed_at":"2026-08-06T20:33:08.337897Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.11737","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.548286Z","title":"MSATNet: multi-scale adaptive transformer network for motor imagery classification,","venue":null,"work_id":"b138d3b0-d6f6-473d-bfa3-b03d3b967931","year":2023},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.933070Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:1f16540531127351073c01b7911aa162e5ed34b9dd2d9b05c056c8904fe6bc11","observation_id":"338e175d-4304-48cf-a3f4-bb9609c57150","resolution":{"observed_at":"2026-08-06T20:33:07.554630Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/sim.7263","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.022874Z","title":"Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method,","venue":null,"work_id":"f0caf752-4559-4e58-9d1f-61a04a5cde57","year":2017},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.936513Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:a7d38b4fe643ed5383f9b489128fefd77b14d55b8b7e04db0dafae7bf26bd0d7","observation_id":"c47cb413-3589-4214-be8e-7925c7497212","resolution":{"observed_at":"2026-08-06T20:33:07.027496Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.940220Z","title":"Deep Learning for EEG motor imagery classification based on multi -layer CNNs feature fusion,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.940220Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:3d100a6b6dbb76988560b608f417f056ae241d14cf7539140c513fd846efbde0","observation_id":"d85bf9da-0d2c-43af-b2af-2b223fce8f14","resolution":{"observed_at":"2026-08-06T20:33:06.940220Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:06.943708Z","title":"EISATC -Fusion: Inception Self - Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.943708Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:27d6c7a3c0e5c64170555f16ccdb5ef6107d38dfcae7c360b30246ac8c4a1037","observation_id":"0aa606dc-4387-4678-823f-a8af8c2046c7","resolution":{"observed_at":"2026-08-06T20:33:06.943708Z","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":"2021.82543","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:07.358191Z","title":"Seizure Prediction in EEG Signals Using STFT and Domain Adaptation,","venue":null,"work_id":"6d81d868-e720-4040-a230-e2e3c095c139","year":2022},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.947324Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:2e2a8c0234bda5960a62d4e02573669351ceccaf73ffdd6420c7675c60df149d","observation_id":"6656ef0b-3b8a-4696-99c0-033a7d5e7e74","resolution":{"observed_at":"2026-08-06T20:33:07.365515Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11517","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:06.996986Z","title":"EEG classification across sessions and across subjects through transfer learning in motor imagery -based brain-machine interface system,","venue":null,"work_id":"c6d368c3-9d68-47ab-97b8-f9221852d369","year":2020},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.951201Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:7b339bc7b2c2bab2db9050d94b810b8859fa82901007f2dfeded0d5dc0314e52","observation_id":"bf38ed34-ee68-4acb-be64-78bf36020442","resolution":{"observed_at":"2026-08-06T20:33:07.003546Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T20:33:06.955163Z","title":"Improving cross -subject classification performance of motor imagery signals: a data augmentation -focused deep learning framework,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.955163Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:0759a3ceccba7710b257b6c012d13b524c5ce7d71e2af07510328cfef50ecb2d","observation_id":"f3a31c7f-681b-4f9f-a63d-0c30ad51646b","resolution":{"observed_at":"2026-08-06T20:33:06.955163Z","resolver_source":null,"status":"malformed_identifier"},"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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:33:06.793258Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.793258Z"},"links":{"citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:d8c087cedde16602ffbadb012cdf115d57057537ae8bdd6713d113ef2978b734","observation_id":"a44cb329-6c32-47ea-b661-53dbb07e8a1c","resolution":{"observed_at":"2026-08-06T20:33:06.793258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.15853","last_updated":"2021-12-27T01:55:05Z","snapshot_observed_at":"2026-07-06T11:24:29.655266Z","submitted_at":"2021-06-30T07:18:00Z","title":"Understanding and Improving Early Stopping for Learning with Noisy Labels","version":2},"cited_work":{"arxiv_id":"2106.15853","doi":null,"metadata_source":"pith","pith_arxiv_id":"2106.15853","snapshot_observed_at":"2026-08-06T20:33:07.571037Z","title":"Understanding and Improving Early Stopping for Learning with Noisy Labels","venue":"cs.LG","work_id":"fc215062-c93f-4120-b791-df9f7b22d3c6","year":2021},"citing_paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T20:33:06.928889Z"},"links":{"cited_paper":"/paper/2106.15853","citing_paper":"/paper/2507.02510"},"observation_digest":"sha256:b3a064e267d5f23f8ea873fc0eac627e9ad150d148e5f341776600a255d230f7","observation_id":"d3511dcd-89d1-460f-b248-a5df9e08928e","resolution":{"observed_at":"2026-08-06T20:33:07.575222Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.02510","last_updated":"2025-07-03T10:17:39Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T20:25:02.097751Z","submitted_at":"2025-07-03T10:17:39Z","title":"TFOC-Net: A Short-time Fourier Transform-based Deep Learning Approach for Enhancing Cross-Subject Motor Imagery Classification"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":4,"metadata_mismatch":5,"parse_uncertain":0,"unresolved":13,"verified_exact":15,"verified_fuzzy":6},"total_outbound_references":43},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.02510."}