{"as_of":"2026-08-23T14:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:be5ebf58e28768eb3a8b26b194745a1edde08438bcd49f942bc632eff7533030","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-24T23:35:37.808211Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/1907.04888/citation-record","integrity":"/paper/1907.04888/integrity","json":"/paper/1907.04888/citation-record.json","paper":"/paper/1907.04888"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Accessed: 2017","venue":null,"work_id":"e74097ce-f820-409c-8e95-c674b55fcb3d","year":2017},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:a2b71d2993332657742051d913608e617067ab2feb4cf0c89be38b87da422aa3","observation_id":"87ba221e-0e48-482d-bd2a-c76baa0a663b","resolution":{"observed_at":"2026-05-24T23:36:27.930548Z","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":"2026-06-05T21:23:00.469572Z","title":"Deep learning based isolated arabic scene character recognition","venue":null,"work_id":"d512c135-7807-4ada-b2d1-644e68296b9c","year":2017},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:7ac49de70ad67ae4e2068e707687e505b4517544f62e9a825699057cd0815108","observation_id":"23136d58-daec-4d62-935a-cf96c3568a6b","resolution":{"observed_at":"2026-05-24T23:36:27.861034Z","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":"2026-06-05T21:23:00.469572Z","title":"Rimes evaluation campaign for handwritten mail processing","venue":null,"work_id":"650d9224-6ad6-44c6-8b2e-1aeae13c4fc3","year":2006},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:2b2ceeaa16080c6defec941ac65b7fea1dee95fc236e75412d8e5228e33342b6","observation_id":"242f5357-3c7e-4bb2-94c5-738c9322bf0e","resolution":{"observed_at":"2026-05-24T23:36:27.921881Z","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":"2026-06-05T21:23:00.469572Z","title":"Handwritten text recognition using deep learning","venue":null,"work_id":"af8e0f68-ad76-41e1-8233-1d3ee131587f","year":2017},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:fd7514fc10ade177c6c849a05e7ca56c3c0a37fac1c0bfcf4dc4fe5894da6d47","observation_id":"f510bd81-c285-4bf9-a23f-fb6cc5e0428f","resolution":{"observed_at":"2026-05-24T23:36:27.945333Z","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":"2026-06-05T21:23:00.469572Z","title":"A comparison of sequence-trained deep neural networks and recurrent neural networks optical modeling for handwriting recognition","venue":null,"work_id":"96672eb4-e35e-4e8b-8837-3c60698a77b6","year":2014},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:26c4dfe0d114929551e5d911c7d61accaaea609a47e680a393cdcfdaf6b60c63","observation_id":"0081cd0f-00fa-494b-97e2-bec6b52dd3fd","resolution":{"observed_at":"2026-05-24T23:36:27.889028Z","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":"2026-06-05T21:23:00.469572Z","title":"Structured document segmentation and representation by the modiﬁed xy tree","venue":null,"work_id":"9c1e33e1-0f14-4a69-9b46-052a3cdb01d7","year":1999},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:3ff3a8ca5043d0a18e18eb5dace8605b132b6c795f71e69eb7e0d2e950296697","observation_id":"8774f3f5-1a1e-4ed4-9dab-dadf31083bb9","resolution":{"observed_at":"2026-05-24T23:36:27.910707Z","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":"1606.00915","last_updated":"2017-05-12T03:25:47Z","snapshot_observed_at":"2026-08-16T22:55:31.005114Z","submitted_at":"2016-06-02T21:52:21Z","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","version":2},"cited_work":{"arxiv_id":"1606.00915","doi":null,"metadata_source":"pith","pith_arxiv_id":"1606.00915","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs","venue":"cs.CV","work_id":"e09101fa-3863-4b7a-90c2-5a47fc265ba6","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"cited_paper":"/paper/1606.00915","citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:db5f33e59c1aad510a5358b2f871f37bffb7af095f667f822d78b7ee7430c4e8","observation_id":"c631847c-1f35-42f4-a057-ed0941a356ee","resolution":{"observed_at":"2026-05-24T23:36:27.635157Z","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":"2026-06-05T21:23:00.469572Z","title":"A system for ofﬂine character recognition using auto-encoder networks","venue":null,"work_id":"880a2f68-1fdf-4e39-9dec-7f6abf964d4c","year":2012},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:dedb8a012bd7620cb71f7c2412039892f99248f7caa672eeff1498623fa55a70","observation_id":"d7d19961-fa31-4a93-ba81-e994c0a78e75","resolution":{"observed_at":"2026-05-24T23:36:27.917926Z","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":"2026-06-05T21:23:00.469572Z","title":"Fast and robust training of recurrent neural networks for ofﬂine handwriting recogni- tion","venue":null,"work_id":"2383755f-705f-4611-a845-aab649694769","year":2014},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:381664e34963c1e428fe0ed45de99c42de4fc56629d6a07ec7ec9e89d66be2f6","observation_id":"839beba1-d949-4cff-a377-64b61fb7b524","resolution":{"observed_at":"2026-05-24T23:36:27.903106Z","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":"2026-06-05T21:23:00.469572Z","title":"Hierarchical hybrid mlp/hmm or rather mlp features for a discrimi- natively trained gaussian hmm: a comparison for ofﬂine handwriting recognition","venue":null,"work_id":"437283b6-e8f4-4a56-a33a-ffc1e2097f4b","year":2011},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:20e8bc18f35e229abc7375f8e66c37c7261a9337a65813e097cae254274f7419","observation_id":"db54f90e-d0b2-4fa1-b78e-5366b884d07a","resolution":{"observed_at":"2026-05-24T23:36:27.889594Z","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":"2026-06-05T21:23:00.469572Z","title":"Improving ofﬂine handwritten text recognition with hybrid hmm/ann models","venue":null,"work_id":"353b28fe-bc88-43b8-a6fc-4f3b3dc175af","year":2011},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:03dd06126ed5d85ecd283a06bbeb2bb6b2aeb33edbcc658b2476331b0700eec9","observation_id":"511fe7ca-5062-4f25-95e4-5c298d96a1e2","resolution":{"observed_at":"2026-05-24T23:36:27.938007Z","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":"2026-06-05T21:23:00.469572Z","title":"Handwritten word recognition with character and inter-character neural networks","venue":null,"work_id":"951aca7a-3038-4d2f-9309-94508dc91abe","year":1997},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:2ca2ec81903b1f7bcb87885d604838f6630f5b56c6419ed5d7c557ca58590288","observation_id":"fa93acef-f2f7-46ed-b44d-f618927afd4d","resolution":{"observed_at":"2026-05-24T23:36:27.903517Z","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":"2026-06-05T21:23:00.469572Z","title":"Connectionist temporal classiﬁcation: labelling unseg- mented sequence data with recurrent neural networks","venue":null,"work_id":"480fb9aa-bf76-4f69-8a74-3e76a2e079af","year":null},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:18a2988748f7163c966b2b4a84270535e0078543b5351da6275b5292002342ca","observation_id":"69a111aa-bab0-4273-b961-89e6f1aacbb1","resolution":{"observed_at":"2026-05-24T23:36:27.958313Z","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":"2026-06-05T21:23:00.469572Z","title":"Long short-term memory","venue":null,"work_id":"a1b777dd-3287-4d2b-92e6-2e204641af55","year":1997},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:ac441bf7353ab8f2f7c402fe77503e6899773708c35a82a016ec764ffe507849","observation_id":"530ecd4c-4eb2-4dd8-9d8c-5ee4fd06247d","resolution":{"observed_at":"2026-05-24T23:36:27.913835Z","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":"2026-06-05T21:23:00.469572Z","title":"Word segmentation of off-line handwritten documents","venue":null,"work_id":"cd21a79c-6e42-4a14-bd8b-6440ecb96a06","year":2008},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:5a110326fc79d46d87084a314ec151f1bf2a9af2874c4a0d83d5890fd646ddbf","observation_id":"bc564e7e-f6ee-4f35-8d29-c8c1b16b347a","resolution":{"observed_at":"2026-05-24T23:36:27.900020Z","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":"1406.2227","last_updated":"2014-12-09T11:22:59Z","snapshot_observed_at":"2026-08-20T16:25:52.077979Z","submitted_at":"2014-06-09T15:53:33Z","title":"Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition","version":4},"cited_work":{"arxiv_id":"1406.2227","doi":null,"metadata_source":"pith","pith_arxiv_id":"1406.2227","snapshot_observed_at":"2026-07-04T15:59:57.294323Z","title":"Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition","venue":"cs.CV","work_id":"62886c0f-be0b-4a77-80f7-5ae413b76ef0","year":2014},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"cited_paper":"/paper/1406.2227","citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:26470c02dc6c8003cb7a7c01430602e03ed19f838fea49a95a8bf1cc070e6070","observation_id":"67daee99-50f3-44a6-bfda-57aa836edde2","resolution":{"observed_at":"2026-05-24T23:36:27.630251Z","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":"2026-06-05T21:23:00.469572Z","title":"Caffe: Convolutional architecture for fast feature embedding","venue":null,"work_id":"16fc2855-8184-4d3a-9c07-c9d27abcc35e","year":2014},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:0c65dca2922e41c2fb782abdc37d78045243865a80680635725123bd4972d709","observation_id":"a1c71d96-8929-481a-b56e-27d8f04222c7","resolution":{"observed_at":"2026-05-24T23:36:27.930050Z","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":"2026-06-05T21:23:00.469572Z","title":"Improvements in rwth’s system for off-line handwriting recognition","venue":null,"work_id":"ddf35d00-3821-4128-885a-321b52e9c1c2","year":2013},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:fc95792938fcffe50f05420db4e904dff93353733dd329c0f2e7d617b76349b1","observation_id":"849be5b6-a8a8-47df-81a0-bac8d97184ef","resolution":{"observed_at":"2026-05-24T23:36:27.892458Z","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":"2026-06-05T21:23:00.469572Z","title":"Fully convo- lutional networks for semantic segmentation","venue":null,"work_id":"92530f3c-2429-4aea-a974-63f33bb0000d","year":2015},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:9cf6576f91b81d5943cfad56a0a76745c5fea17c95ae2ed96e8ee113aaa4bc9c","observation_id":"dcd5273a-94af-4a46-8ca1-f2a12a9c06e8","resolution":{"observed_at":"2026-05-24T23:36:27.950150Z","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":"2026-06-05T21:23:00.469572Z","title":"The iam-database: an english sentence database for ofﬂine handwriting recognition","venue":null,"work_id":"dd3f5024-1b0e-4401-b445-2c2fd527500e","year":2002},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:79f0f5daa3537f5bf4055840b638746306ad50fb8064df9467b9e392f8791f75","observation_id":"cfee1e52-6de9-490e-a559-ffddeb50fd99","resolution":{"observed_at":"2026-05-24T23:36:27.926654Z","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":"2026-06-05T21:23:00.469572Z","title":"The a2ia french handwriting recognition system at the rimes-icdar2011 competition","venue":null,"work_id":"2f277fd1-1a1a-4a4f-96ed-792627e5274a","year":2012},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:056c8a788b06229d8cbd1298551e2e09796b9580fc21688c8063384ed3d9afe2","observation_id":"6657766c-8f08-48b1-aa98-456f05bc6fc5","resolution":{"observed_at":"2026-05-24T23:36:27.867504Z","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":"2026-06-05T21:23:00.469572Z","title":"Dropout improves recurrent neural networks for hand- writing recognition","venue":null,"work_id":"2cef678b-faf7-4eb3-9cc6-490dac17f357","year":2014},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:3317a3a15f21010049ccb5087e4acccccb30f56c15df7feea7a4a3beb0fe9277","observation_id":"8581440f-32ca-4050-a0b3-28961e5e5c74","resolution":{"observed_at":"2026-05-24T23:36:27.934259Z","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":"2026-06-05T21:23:00.469572Z","title":"Cnn-n-gram for handwriting word recognition","venue":null,"work_id":"bcd0f68a-f46c-418d-b2b2-3c4c300169ed","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:ee8adaf79bedcfe826e1a538211bef241c2f9089a740eb4be49905b4e2415fe7","observation_id":"e800217c-b1a8-4159-8480-e48f710077da","resolution":{"observed_at":"2026-05-24T23:36:27.920334Z","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":"2026-06-05T21:23:00.469572Z","title":"Faster r- cnn: Towards real-time object detection with region proposal networks","venue":null,"work_id":"ed70268f-b1f3-45a1-a8ef-d7430a7c2471","year":2015},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:03cbc7b9f37423057c571ede94ad1592fbd9a96eb56af8f57376dcf1115e12b2","observation_id":"d805ebb5-bac3-4214-be1c-2fd33293f5ad","resolution":{"observed_at":"2026-05-24T23:36:27.917155Z","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":"2026-06-05T21:23:00.469572Z","title":"An end-to-end trainable neural network for image-based sequence recognition and its applica- tion to scene text recognition","venue":null,"work_id":"a3376df1-5ab7-4151-b797-d40c93624711","year":2017},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:3177bd99a24f4cf9b74d22d0ce1c8216bd5149a1a325ce1d284f91180d892505","observation_id":"1647a6c4-ab7a-4091-9369-4c91d372c356","resolution":{"observed_at":"2026-05-24T23:36:27.906735Z","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":"2026-06-05T21:23:00.469572Z","title":"Robust scene text recognition with automatic rectiﬁcation","venue":null,"work_id":"b61d53fe-2c93-4808-8eb1-54686b410f81","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:64b16b55e451a8211a7419018f587a6eb90abc93ba1ceca1119ac8193f80a207","observation_id":"e3c78c32-ea0c-48a3-9546-44fef7c62089","resolution":{"observed_at":"2026-05-24T23:36:27.926047Z","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":"2026-06-05T21:23:00.469572Z","title":"An analysis of sentence boundary detection systems for english and portuguese documents","venue":null,"work_id":"8f74dcbe-4770-4a55-afc5-52de3aa5d643","year":2004},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:8b94b650a5ed226c599d5978b127d6c071283b134d0835076baacaea13bca404","observation_id":"6a2ed901-8678-4a12-b6e8-16ba0fbb0265","resolution":{"observed_at":"2026-05-24T23:36:27.914209Z","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":"2026-06-05T21:23:00.469572Z","title":"Convolutional multi-directional recurrent network for ofﬂine handwritten text recognition","venue":null,"work_id":"6bf280ec-966e-4377-b0f1-aa7de895881c","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:6cd16395c5e34ae5fc361c326d0213ff85c21b7cb4e1499c7a7200f7b67b216f","observation_id":"3ae0cdf4-b989-407b-b0b0-c6e4630c5cfb","resolution":{"observed_at":"2026-05-24T23:36:27.871341Z","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":"2026-06-05T21:23:00.469572Z","title":"Feature extraction methods for character recognition-a survey","venue":null,"work_id":"b258ec41-d57d-4b7f-9949-0c6bc4d18e11","year":1996},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:efb231b2885dbd86987537a1267625aa20dd21c30ddb0b7aef0e8a74779a379b","observation_id":"494feb4c-c5b4-4ee2-8d1f-063185917bfb","resolution":{"observed_at":"2026-05-24T23:36:27.954183Z","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":"2026-06-05T21:23:00.469572Z","title":"Handwriting recognition with large multidimensional long short-term memory re- current neural networks","venue":null,"work_id":"34f0f299-fbfa-46b0-b27e-f86032d21b8f","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:b3b9b22b3f155328ddc849cedcf66f46739b2b4f2cf1753a37f79e2529ba10d7","observation_id":"1b2d78f6-01e4-4678-a432-6ff55dee6001","resolution":{"observed_at":"2026-05-24T23:36:27.885950Z","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":"2026-06-05T21:23:00.469572Z","title":"Fully convolutional recurrent network for handwritten chinese text recognition","venue":null,"work_id":"81d54776-4e3f-4577-b9e1-497220576858","year":2016},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:0cbe87446bf927e185784616d2e1d05276bf3c15da775b168062aefd21185be7","observation_id":"6bc1d8cd-a47a-4afc-875c-b271a57c5ab7","resolution":{"observed_at":"2026-05-24T23:36:27.878925Z","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":"2026-06-05T21:23:00.469572Z","title":"A deep learning based character recognition system from multimedia document","venue":null,"work_id":"c106dd78-2871-4dd7-8d85-97168a0181fb","year":2017},"citing_paper":{"arxiv_id":"1907.04888","last_updated":"2019-07-10T18:54:27Z","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-24T23:35:37.808211Z"},"links":{"citing_paper":"/paper/1907.04888"},"observation_digest":"sha256:2a66bbe8db030528fe680b62a59f50d8ab8892f1f53b755b4b91acaaa639341a","observation_id":"967afad0-d2a3-4f07-ae7c-23572064bbb1","resolution":{"observed_at":"2026-05-24T23:36:27.875056Z","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":"1907.04888","last_updated":"2019-07-10T18:54:27Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-19T05:51:41.328082Z","submitted_at":"2019-07-10T18:54:27Z","title":"Fully Convolutional Networks for Handwriting Recognition"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":30},"total_outbound_references":32},"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 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:1907.04888."}