{"id":"https://openalex.org/W2963047498","doi":"https://doi.org/10.1109/tpami.2017.2695539","title":"Drawing and Recognizing Chinese Characters with Recurrent Neural Network","display_name":"Drawing and Recognizing Chinese Characters with Recurrent Neural Network","publication_year":2017,"publication_date":"2017-04-18","ids":{"openalex":"https://openalex.org/W2963047498","doi":"https://doi.org/10.1109/tpami.2017.2695539","mag":"2963047498","pmid":"https://pubmed.ncbi.nlm.nih.gov/28436845"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2017.2695539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2695539","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5082548671","display_name":"Xu-Yao Zhang","orcid":"https://orcid.org/0000-0001-9260-188X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu-Yao Zhang","raw_affiliation_strings":["NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039310938","display_name":"Fei Yin","orcid":"https://orcid.org/0000-0002-6412-9140"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Yin","raw_affiliation_strings":["NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604282","display_name":"Yan\u2010Ming Zhang","orcid":"https://orcid.org/0000-0001-6718-5589"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan-Ming Zhang","raw_affiliation_strings":["NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100714202","display_name":"Cheng\u2010Lin Liu","orcid":"https://orcid.org/0000-0002-6743-4175"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng-Lin Liu","raw_affiliation_strings":["NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"NLPR, Chinese Academy of Sciences, Beijing, P.R.\u00a0China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086198262","display_name":"Yoshua Bengio","orcid":"https://orcid.org/0000-0002-9322-3515"},"institutions":[{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yoshua Bengio","raw_affiliation_strings":["MILA Lab, University of Montreal, Montreal, QC, Canada"],"affiliations":[{"raw_affiliation_string":"MILA Lab, University of Montreal, Montreal, QC, Canada","institution_ids":["https://openalex.org/I70931966"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082548671"],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":13.5043,"has_fulltext":false,"cited_by_count":353,"citation_normalized_percentile":{"value":0.99148685,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"40","issue":"4","first_page":"849","last_page":"862"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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":1.0,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9918000102043152,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9821000099182129,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.8232647180557251},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8112616539001465},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.798224687576294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7360605597496033},{"id":"https://openalex.org/keywords/handwriting","display_name":"Handwriting","score":0.718951404094696},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.6427868604660034},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5334722399711609},{"id":"https://openalex.org/keywords/handwriting-recognition","display_name":"Handwriting recognition","score":0.5238359570503235},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5089974403381348},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48768889904022217},{"id":"https://openalex.org/keywords/intelligent-character-recognition","display_name":"Intelligent character recognition","score":0.4607710540294647},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4223794639110565},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4206065535545349},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.41925501823425293},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41215071082115173},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40806227922439575},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3617090582847595},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.33735597133636475},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3336198329925537},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.2771039605140686},{"id":"https://openalex.org/keywords/character-recognition","display_name":"Character recognition","score":0.1732882261276245},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17253819108009338}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.8232647180557251},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8112616539001465},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.798224687576294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7360605597496033},{"id":"https://openalex.org/C2779386606","wikidata":"https://www.wikidata.org/wiki/Q2393642","display_name":"Handwriting","level":2,"score":0.718951404094696},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.6427868604660034},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5334722399711609},{"id":"https://openalex.org/C112640561","wikidata":"https://www.wikidata.org/wiki/Q2440634","display_name":"Handwriting recognition","level":3,"score":0.5238359570503235},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5089974403381348},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48768889904022217},{"id":"https://openalex.org/C44868376","wikidata":"https://www.wikidata.org/wiki/Q3099089","display_name":"Intelligent character recognition","level":4,"score":0.4607710540294647},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4223794639110565},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4206065535545349},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.41925501823425293},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41215071082115173},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40806227922439575},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3617090582847595},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33735597133636475},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3336198329925537},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2771039605140686},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.1732882261276245},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17253819108009338},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2017.2695539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2017.2695539","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:28436845","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28436845","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3131366866","display_name":null,"funder_award_id":"61573355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6344653205","display_name":null,"funder_award_id":"61403380","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":85,"referenced_works":["https://openalex.org/W242877468","https://openalex.org/W581956982","https://openalex.org/W1498436455","https://openalex.org/W1514535095","https://openalex.org/W1521968289","https://openalex.org/W1522301498","https://openalex.org/W1606347560","https://openalex.org/W1810943226","https://openalex.org/W1923211482","https://openalex.org/W1924770834","https://openalex.org/W1959608418","https://openalex.org/W1968995181","https://openalex.org/W1978964824","https://openalex.org/W1998318956","https://openalex.org/W2004767896","https://openalex.org/W2033404582","https://openalex.org/W2062361515","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2096252661","https://openalex.org/W2099471712","https://openalex.org/W2100495367","https://openalex.org/W2100721436","https://openalex.org/W2107878631","https://openalex.org/W2111364271","https://openalex.org/W2112796928","https://openalex.org/W2114120312","https://openalex.org/W2115675483","https://openalex.org/W2117480013","https://openalex.org/W2119305530","https://openalex.org/W2119818729","https://openalex.org/W2122585011","https://openalex.org/W2127141656","https://openalex.org/W2131774270","https://openalex.org/W2135181320","https://openalex.org/W2136848157","https://openalex.org/W2140090592","https://openalex.org/W2142069714","https://openalex.org/W2143246460","https://openalex.org/W2156338447","https://openalex.org/W2157331557","https://openalex.org/W2160511393","https://openalex.org/W2170866695","https://openalex.org/W2173520492","https://openalex.org/W2237532981","https://openalex.org/W2269752429","https://openalex.org/W2418519490","https://openalex.org/W2586915103","https://openalex.org/W2916727894","https://openalex.org/W2919115771","https://openalex.org/W2949191843","https://openalex.org/W2950527759","https://openalex.org/W2951523806","https://openalex.org/W2962741254","https://openalex.org/W2962779710","https://openalex.org/W2963684088","https://openalex.org/W2964121744","https://openalex.org/W3099884890","https://openalex.org/W4285719527","https://openalex.org/W4302061398","https://openalex.org/W4303633609","https://openalex.org/W4320013936","https://openalex.org/W6609220935","https://openalex.org/W6616837769","https://openalex.org/W6621378261","https://openalex.org/W6630875275","https://openalex.org/W6631143415","https://openalex.org/W6631190155","https://openalex.org/W6636358008","https://openalex.org/W6638273328","https://openalex.org/W6639118987","https://openalex.org/W6640212811","https://openalex.org/W6640963894","https://openalex.org/W6651575327","https://openalex.org/W6674330103","https://openalex.org/W6676533897","https://openalex.org/W6677886537","https://openalex.org/W6680498451","https://openalex.org/W6681142079","https://openalex.org/W6684821475","https://openalex.org/W6685352114","https://openalex.org/W6693848384","https://openalex.org/W6694605516","https://openalex.org/W6732742072","https://openalex.org/W6732980938"],"related_works":["https://openalex.org/W3199359807","https://openalex.org/W4386428871","https://openalex.org/W2378345698","https://openalex.org/W3047607512","https://openalex.org/W3003949997","https://openalex.org/W4390983538","https://openalex.org/W2110485610","https://openalex.org/W183832189","https://openalex.org/W2099822426","https://openalex.org/W2406729210"],"abstract_inverted_index":{"Recent":[0],"deep":[1],"learning":[2],"based":[3,120],"approaches":[4],"have":[5],"achieved":[6,153],"great":[7],"success":[8],"on":[9,30,154],"handwriting":[10,112],"recognition.":[11],"Chinese":[12,33,59,82,91,95,177,221],"characters":[13,83,181],"are":[14,185],"among":[15],"the":[16,23,70,101,110,130,141,155,161,193,203,215],"most":[17],"widely":[18],"adopted":[19],"writing":[20],"systems":[21],"in":[22],"world.":[24],"Previous":[25],"research":[26],"has":[27],"mainly":[28],"focused":[29],"recognizing":[31,81,220],"handwritten":[32],"characters.":[34,60,92,178,222],"However,":[35],"recognition":[36],"is":[37,50,122,171],"only":[38],"one":[39],"aspect":[40],"for":[41,80,88,173,214],"understanding":[42],"a":[43,53,66,77,85,164],"language,":[44],"another":[45],"challenging":[46],"and":[47,84,133,147,187,211,219],"interesting":[48],"task":[49],"to":[51,55],"teach":[52],"machine":[54],"automatically":[56,174],"write":[57],"(pictographic)":[58],"In":[61],"this":[62],"paper,":[63],"we":[64],"propose":[65],"framework":[67],"by":[68,192],"using":[69,206],"recurrent":[71],"neural":[72,103],"network":[73,104],"(RNN)":[74],"as":[75,208],"both":[76,209],"discriminative":[78,194,212],"model":[79,87,167,196],"generative":[86,166,210],"drawing":[89,175,218],"(generating)":[90],"To":[93],"recognize":[94],"characters,":[96],"previous":[97],"methods":[98],"usually":[99],"adopt":[100],"convolutional":[102],"(CNN)":[105],"models":[106,213],"which":[107,126],"require":[108,136],"transforming":[109],"online":[111],"trajectory":[113],"into":[114],"image-like":[115],"representations.":[116],"Instead,":[117],"our":[118],"RNN":[119,142,162,195],"approach":[121],"an":[123,145],"end-to-end":[124],"system":[125,143],"directly":[127],"deals":[128],"with":[129,168,197],"sequential":[131],"structure":[132],"does":[134],"not":[135],"any":[137],"domain-specific":[138],"knowledge.":[139],"With":[140],"(combining":[144],"LSTM":[146],"GRU),":[148],"state-of-the-art":[149],"performance":[150],"can":[151,189],"be":[152,190],"ICDAR-2013":[156],"competition":[157],"database.":[158],"Furthermore,":[159],"under":[160],"framework,":[163],"conditional":[165],"character":[169],"embedding":[170],"proposed":[172],"recognizable":[176],"The":[179],"generated":[180],"(in":[182],"vector":[183],"format)":[184],"human-readable":[186],"also":[188],"recognized":[191],"high":[198],"accuracy.":[199],"Experimental":[200],"results":[201],"verify":[202],"effectiveness":[204],"of":[205,217],"RNNs":[207],"tasks":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":34},{"year":2023,"cited_by_count":43},{"year":2022,"cited_by_count":54},{"year":2021,"cited_by_count":51},{"year":2020,"cited_by_count":50},{"year":2019,"cited_by_count":46},{"year":2018,"cited_by_count":40},{"year":2017,"cited_by_count":10}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}