{"id":"https://openalex.org/W2806717845","doi":"https://doi.org/10.1109/tmm.2018.2844689","title":"Track, Attend, and Parse (TAP): An End-to-End Framework for Online Handwritten Mathematical Expression Recognition","display_name":"Track, Attend, and Parse (TAP): An End-to-End Framework for Online Handwritten Mathematical Expression Recognition","publication_year":2018,"publication_date":"2018-06-06","ids":{"openalex":"https://openalex.org/W2806717845","doi":"https://doi.org/10.1109/tmm.2018.2844689","mag":"2806717845"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2018.2844689","doi":"https://doi.org/10.1109/tmm.2018.2844689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2018.2844689","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-a","cwts-core","dongbi-a","jufo-3","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W2806717845"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101760682","display_name":"Jianshu Zhang","orcid":"https://orcid.org/0000-0002-2713-2535","observed_orcids":["https://orcid.org/0000-0002-2713-2535"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianshu Zhang","raw_affiliation_strings":["National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":"https://orcid.org/0000-0002-2713-2535","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066595711","display_name":"Jun Du","orcid":"https://orcid.org/0000-0002-2387-0389","observed_orcids":["https://orcid.org/0000-0002-2387-0389","https://orcid.org/0009-0001-8096-9895"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Du","raw_affiliation_strings":["National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":"https://orcid.org/0000-0002-2387-0389","affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057227915","display_name":"Li-Rong Dai","orcid":"https://orcid.org/0000-0002-0859-2827","observed_orcids":["https://orcid.org/0000-0002-0859-2827"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lirong Dai","raw_affiliation_strings":["National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Speech and Language Information Processing, University of Science and Technology of China, Hefei, Anhui, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":6.9742,"has_fulltext":false,"cited_by_count":131,"citation_normalized_percentile":{"value":0.97662619,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"21","issue":"1","first_page":"221","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13523","display_name":"Mathematics, Computing, and Information Processing","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory-tracking","display_name":"trajectory tracking","score":0.5220000147819519},{"id":"https://openalex.org/keywords/expression-parsing","display_name":"expression parsing","score":0.625},{"id":"https://openalex.org/keywords/temporal-attention","display_name":"temporal attention","score":0.8059999942779541},{"id":"https://openalex.org/keywords/attentional-guidance","display_name":"attention guidance","score":0.44699999690055847},{"id":"https://openalex.org/keywords/bidirectional-recurrent-neural-network","display_name":"bidirectional recurrent neural network","score":0.7519999742507935},{"id":"https://openalex.org/keywords/gated-recurrent-unit","display_name":"gated recurrent unit","score":0.9319999814033508},{"id":"https://openalex.org/keywords/fully-convolutional-network","display_name":"fully convolutional network","score":0.7329999804496765},{"id":"https://openalex.org/keywords/end-to-end-recognition","display_name":"end-to-end recognition","score":0.7570000290870667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.885201096534729},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7440240383148193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5921093225479126},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5745003819465637},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4850851595401764},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.43388283252716064},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.4284961223602295},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4251716434955597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41770797967910767},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36411356925964355},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3281763195991516}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2018.2844689","doi":"https://doi.org/10.1109/tmm.2018.2844689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2018.2844689","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["ccf-a","cwts-core","dongbi-a","jufo-3","norway-1","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G573022218","display_name":null,"funder_award_id":"U1613211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8173470123","display_name":"\u57fa\u4e8e\u56de\u5f52\u795e\u7ecf\u7f51\u7edc\u7684\u8bed\u97f3\u5206\u79bb\u5173\u952e\u95ee\u9898\u7814\u7a76","funder_award_id":"61671422","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W187324601","https://openalex.org/W1514535095","https://openalex.org/W1534477342","https://openalex.org/W1554656010","https://openalex.org/W1620012354","https://openalex.org/W1686810756","https://openalex.org/W1799103480","https://openalex.org/W1810641085","https://openalex.org/W1895577753","https://openalex.org/W1903029394","https://openalex.org/W1905882502","https://openalex.org/W1923211482","https://openalex.org/W1924770834","https://openalex.org/W1978799108","https://openalex.org/W1981451828","https://openalex.org/W1998768285","https://openalex.org/W2005079280","https://openalex.org/W2019370496","https://openalex.org/W2026012689","https://openalex.org/W2037121285","https://openalex.org/W2047964964","https://openalex.org/W2049035241","https://openalex.org/W2071291967","https://openalex.org/W2072449446","https://openalex.org/W2078396547","https://openalex.org/W2080193993","https://openalex.org/W2080213370","https://openalex.org/W2107878631","https://openalex.org/W2108677974","https://openalex.org/W2109886035","https://openalex.org/W2118434577","https://openalex.org/W2122710056","https://openalex.org/W2123119958","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2139186315","https://openalex.org/W2143612262","https://openalex.org/W2143648950","https://openalex.org/W2150693620","https://openalex.org/W2152175008","https://openalex.org/W2156286766","https://openalex.org/W2157331557","https://openalex.org/W2163605009","https://openalex.org/W2170570264","https://openalex.org/W2178333206","https://openalex.org/W2302043111","https://openalex.org/W2327501763","https://openalex.org/W2514009036","https://openalex.org/W2528252828","https://openalex.org/W2574045079","https://openalex.org/W2575842049","https://openalex.org/W2623860192","https://openalex.org/W2735673432","https://openalex.org/W2739107216","https://openalex.org/W2754689878","https://openalex.org/W2963047498","https://openalex.org/W2963181957","https://openalex.org/W2963260202","https://openalex.org/W2963311793","https://openalex.org/W2963630207","https://openalex.org/W2963901427","https://openalex.org/W2964108850","https://openalex.org/W2964308564","https://openalex.org/W4322695928","https://openalex.org/W6678074473","https://openalex.org/W6681483957","https://openalex.org/W6996569244","https://openalex.org/W7028957390","https://openalex.org/W7048411397"],"related_works":["https://openalex.org/W2964108850","https://openalex.org/W2623860192","https://openalex.org/W2140293704","https://openalex.org/W3004194266","https://openalex.org/W3217181631","https://openalex.org/W4285287761","https://openalex.org/W4313125865","https://openalex.org/W4395449500","https://openalex.org/W4412787091","https://openalex.org/W3160928960"],"abstract_inverted_index":{"In":[0],"this":[1,132],"paper,":[2],"we":[3,102],"introduce":[4],"Track,":[5],"Attend,":[6],"and":[7,32,97,113,142,165,181],"Parse":[8],"(TAP),":[9],"an":[10,98,172],"end-to-end":[11,133],"approach":[12,160],"based":[13],"on":[14,150,178,183],"neural":[15,43],"networks":[16,44],"for":[17,147],"online":[18,114],"handwritten":[19,54],"mathematical":[20],"expression":[21,145,173],"recognition":[22,174],"(OHMER).":[23],"The":[24,35,84],"architecture":[25],"of":[26,29,40,89,176],"TAP":[27],"consists":[28],"a":[30,33,38,73,90,94,121,143,151],"tracker":[31,36],"parser.":[34],"employs":[37],"stack":[39],"bidirectional":[41],"recurrent":[42,47],"with":[45,76,110,116,171],"gated":[46],"units":[48],"(GRU)":[49],"to":[50,81],"model":[51],"the":[52,60,68,70,104,138,155,158,162,167],"input":[53,112,118],"traces,":[55],"which":[56],"can":[57],"fully":[58,122],"utilize":[59],"dynamic":[61],"trajectory":[62],"information":[63,109,115],"in":[64],"OHMER.":[65],"Followed":[66],"by":[67,119,154],"tracker,":[69],"parser":[71],"adopts":[72],"GRU":[74],"equipped":[75],"guided":[77],"hybrid":[78],"attention":[79,99],"(GHA)":[80],"generate":[82],"notations.":[83],"proposed":[85,159],"GHA":[86],"is":[87],"composed":[88],"coverage-based":[91],"spatial":[92],"attention,":[93,96],"temporal":[95],"guider.":[100],"Moreover,":[101],"demonstrate":[103],"strong":[105],"complementarity":[106],"between":[107],"offline":[108],"static-image":[111],"ink-trajectory":[117],"blending":[120],"convolutional":[123],"networks-based":[124],"watcher":[125],"into":[126],"TAP.":[127],"Inherently,":[128],"unlike":[129],"traditional":[130],"methods,":[131],"framework":[134],"does":[135],"not":[136],"require":[137],"explicit":[139],"symbol":[140],"segmentation":[141],"predefined":[144],"grammar":[146],"parsing.":[148],"Validated":[149],"benchmark":[152],"published":[153],"CROHME":[156,179,184],"competition,":[157],"outperforms":[161],"state-of-the-art":[163],"methods":[164],"achieves":[166],"best":[168],"reported":[169],"results":[170],"accuracy":[175],"61.16%":[177],"2014":[180],"57.02%":[182],"2016,":[185],"using":[186],"only":[187],"official":[188],"training":[189],"dataset.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":30},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":10}],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2018-06-13T00:00:00"}