{"id":"https://openalex.org/W4205709198","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660518","title":"Ancient Chinese Recognition Method Based on Attention Mechanism","display_name":"Ancient Chinese Recognition Method Based on Attention Mechanism","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4205709198","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660518"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc54101.2021.9660518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660518","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5017094281","display_name":"Lingjing Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjing Wu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015730388","display_name":"Chuang Zhang","orcid":"https://orcid.org/0000-0002-1115-5580"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuang Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042888894","display_name":"Mengqiu Xu","orcid":"https://orcid.org/0000-0002-3029-7664"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengqiu Xu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077902436","display_name":"Ming Wu","orcid":"https://orcid.org/0000-0001-8390-5398"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Wu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0955,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41801341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"309","last_page":"313"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9869999885559082,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9869999885559082,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9769999980926514,"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/T13568","display_name":"Wood and Agarwood Research","score":0.972599983215332,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7362232208251953},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6577608585357666},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.6557987928390503},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6534172296524048},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6297723650932312},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5857700705528259},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5438731908798218},{"id":"https://openalex.org/keywords/character-recognition","display_name":"Character recognition","score":0.5038506388664246},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4864032566547394},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.4367815852165222},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41733479499816895},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37627682089805603},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1735800802707672},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08687180280685425},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.07480615377426147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7362232208251953},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6577608585357666},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.6557987928390503},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6534172296524048},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6297723650932312},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5857700705528259},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5438731908798218},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.5038506388664246},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4864032566547394},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.4367815852165222},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41733479499816895},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37627682089805603},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1735800802707672},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08687180280685425},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.07480615377426147},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc54101.2021.9660518","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660518","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1849277567","https://openalex.org/W1899185266","https://openalex.org/W1994615285","https://openalex.org/W2035609259","https://openalex.org/W2106843299","https://openalex.org/W2108598243","https://openalex.org/W2127271787","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2221625691","https://openalex.org/W2390331507","https://openalex.org/W2565262489","https://openalex.org/W2962779710","https://openalex.org/W2963163009","https://openalex.org/W6637373629","https://openalex.org/W6639204139","https://openalex.org/W6639927594","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W3019910406","https://openalex.org/W2355248651","https://openalex.org/W1969308216","https://openalex.org/W3139757486","https://openalex.org/W2152317605","https://openalex.org/W2393195031","https://openalex.org/W2149918773","https://openalex.org/W2166484416","https://openalex.org/W2003435449"],"abstract_inverted_index":{"Characters":[0],"and":[1,10,21,34,63],"symbols":[2],"play":[3],"an":[4],"important":[5],"role":[6],"of":[7,36,42,82,128,142],"historical":[8],"development":[9],"cultural":[11],"transmission.":[12],"Automatic":[13],"ancient":[14,46,78],"character":[15,73,117],"recognition":[16,27,96,106],"has":[17,137],"become":[18],"a":[19,111,139],"meaningful":[20],"typical":[22],"task.":[23],"However,":[24],"the":[25,32,43,52,86,125],"existing":[26],"methods":[28,53,69],"mostly":[29],"focus":[30],"on":[31,45,77],"detection":[33],"classification":[35],"modern":[37],"Chinese,":[38,47],"there":[39],"are":[40,54],"lack":[41,70],"research":[44],"especially":[48],"pre-Qin":[49],"characters.":[50,130],"And":[51],"mainly":[55],"computer":[56],"graphics,":[57],"topology,":[58],"support":[59],"vector":[60],"machines":[61],"(SVM)":[62],"convolutional":[64],"neural":[65],"networks":[66],"(CNN),":[67],"these":[68],"attention":[71,93],"to":[72,95,98,104],"features.":[74],"Thus,":[75],"based":[76],"Chinese":[79,129],"characters":[80],"dataset":[81],"Tsinghua":[83],"Bamboo":[84],"Slips,":[85],"method":[87,114,136],"proposed":[88],"in":[89,102],"this":[90],"paper":[91],"add":[92],"mechanism":[94],"algorithms":[97],"replace":[99],"traditional":[100],"convolution":[101],"order":[103],"improve":[105],"accuracy.":[107],"Besides,":[108],"we":[109],"propose":[110],"data":[112],"augmentation":[113],"specifically":[115],"for":[116],"images,":[118],"as":[119,121],"much":[120],"possible":[122],"without":[123],"changing":[124],"writing":[126],"form":[127],"Experimental":[131],"results":[132],"demonstrated":[133],"that":[134],"our":[135],"achieved":[138],"top5":[140],"accuracy":[141],"99.98%":[143],"which":[144],"is":[145],"higher":[146],"compared":[147],"with":[148],"other":[149],"methods.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}