{"id":"https://openalex.org/W2046450072","doi":"https://doi.org/10.1002/cpe.4330020202","title":"Construction of a large\u2010scale neural network: Simulation of handwritten Japanese character recognition on NCUBE","display_name":"Construction of a large\u2010scale neural network: Simulation of handwritten Japanese character recognition on NCUBE","publication_year":1990,"publication_date":"1990-06-01","ids":{"openalex":"https://openalex.org/W2046450072","doi":"https://doi.org/10.1002/cpe.4330020202","mag":"2046450072"},"language":"en","primary_location":{"id":"doi:10.1002/cpe.4330020202","is_oa":false,"landing_page_url":"https://doi.org/10.1002/cpe.4330020202","pdf_url":null,"source":{"id":"https://openalex.org/S4210209928","display_name":"Concurrency Practice and Experience","issn_l":"1040-3108","issn":["1040-3108","1096-9128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrency: Practice and Experience","raw_type":"journal-article"},"type":"article","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/A5110599009","display_name":"Kazuki Joe","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kazuki Joe","raw_affiliation_strings":["ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","institution_ids":[]},{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001031799","display_name":"Yoshihiro Mori","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yoshihiro Mori","raw_affiliation_strings":["ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","institution_ids":[]},{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081396550","display_name":"Sei Miyake","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sei Miyake","raw_affiliation_strings":["ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika-cho, Souraku-gun Kyoto, Japan","institution_ids":[]},{"raw_affiliation_string":"ATR Audirory and Visual Perception Research Laboratories Sanpeidani, Inuidani, Seika\u2010cho, Souraku\u2010gun Kyoto, Japan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110599009"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6066,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.70816912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":"2","first_page":"79","last_page":"107"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9983000159263611,"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":0.9983000159263611,"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/T10320","display_name":"Neural Networks and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/subnetwork","display_name":"Subnetwork","score":0.9623970985412598},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7695417404174805},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6656262278556824},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6132494211196899},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6079825758934021},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.5399591326713562},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5393540263175964},{"id":"https://openalex.org/keywords/neocognitron","display_name":"Neocognitron","score":0.5033897757530212},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.48674798011779785},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4619285464286804},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38938167691230774}],"concepts":[{"id":"https://openalex.org/C2780186347","wikidata":"https://www.wikidata.org/wiki/Q11414","display_name":"Subnetwork","level":2,"score":0.9623970985412598},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7695417404174805},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6656262278556824},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6132494211196899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6079825758934021},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.5399591326713562},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5393540263175964},{"id":"https://openalex.org/C121144440","wikidata":"https://www.wikidata.org/wiki/Q669754","display_name":"Neocognitron","level":4,"score":0.5033897757530212},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.48674798011779785},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4619285464286804},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38938167691230774},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/cpe.4330020202","is_oa":false,"landing_page_url":"https://doi.org/10.1002/cpe.4330020202","pdf_url":null,"source":{"id":"https://openalex.org/S4210209928","display_name":"Concurrency Practice and Experience","issn_l":"1040-3108","issn":["1040-3108","1096-9128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Concurrency: Practice and Experience","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W6198882","https://openalex.org/W2156867668","https://openalex.org/W3036512766","https://openalex.org/W3207342693","https://openalex.org/W4300402905"],"related_works":["https://openalex.org/W1584270863","https://openalex.org/W1595652908","https://openalex.org/W4285294654","https://openalex.org/W2085961337","https://openalex.org/W4282920028","https://openalex.org/W1835926121","https://openalex.org/W1500728581","https://openalex.org/W2386241395","https://openalex.org/W2603525251","https://openalex.org/W350603586"],"abstract_inverted_index":{"Abstract":[0],"This":[1,24,230],"paper":[2],"describes":[3],"how":[4,111,218],"new":[5,206],"learning":[6,81,89],"methods":[7,82,92],"may":[8],"make":[9],"it":[10],"possible":[11],"for":[12,129,237,257],"a":[13,26,51,56,112,138,142,146,205,254,272],"large\u2010scale,":[14],"hierarchical":[15,143,147],"neural":[16,57,114,255],"network":[17,58,115,140,152,164,256,270],"to":[18,59,64,165,217,224],"recognize":[19],"most":[20],"Japanese":[21,34,167],"handwritten":[22,166],"characters.":[23],"is":[25,223],"very":[27,61],"large":[28,139],"and":[29,63,102,132,186,246,264],"complex":[30],"task,":[31],"as":[32,83,216],"the":[33,86,121,149,187,199,225,243,248,258],"character":[35,168,238],"set":[36],"consists":[37],"of":[38,85,105,162,190,227,250,253,260,268],"about":[39,182],"3000":[40],"categories":[41,226],"which":[42,209],"can":[43,54,116],"be":[44,117],"written":[45],"in":[46,137,172,233],"many":[47,194],"different":[48],"ways.":[49],"Such":[50],"difficult":[52],"task":[53,123],"lead":[55],"converge":[60],"slowly":[62],"yield":[65],"recognition":[66,97,104,122,169,235,259],"rates":[67,98],"that":[68,163,228],"are":[69],"uneven":[70],"between":[71],"categories.":[72],"To":[73],"address":[74],"these":[75,135],"problems":[76],"we":[77],"here":[78,241],"propose":[79,204],"five":[80],"modifications":[84],"conventional":[87],"back\u2010propagation":[88],"rule.":[90],"These":[91],"produce":[93],"fast":[94],"convergence,":[95],"even":[96],"over":[99],"all":[100],"categories,":[101],"adequate":[103],"test":[106],"samples.":[107],"We":[108,203,240],"also":[109],"describe":[110,265],"large\u2010scale":[113],"built":[118],"by":[119],"dividing":[120],"into":[124],"several":[125],"subtasks,":[126],"with":[127,141,213],"networks":[128,178,197],"each":[130,157,211],"subtask,":[131],"then":[133],"integrating":[134],"subnetworks":[136],"structure.":[144],"In":[145],"network,":[148],"upper":[150,200],"level":[151,159,177,196,201],"directly":[153],"integrates":[154],"outputs":[155,192],"from":[156,193],"lower":[158,176,195],"network.":[160,202],"Application":[161],"has":[170],"resulted":[171,232],"poor":[173],"recognition,":[174],"because":[175],"do":[179],"not":[180],"know":[181],"unknown":[183],"input":[184,221],"patterns,":[185],"direct":[188],"integration":[189,207],"ambiguous":[191],"confuses":[198],"method":[208,231],"provides":[210],"subnetwork":[212],"more":[214],"information":[215],"close":[219],"an":[220],"pattern":[222],"subnetwork.":[229],"high":[234],"performance":[236,249],"recognition.":[239],"described":[242],"above":[244],"methods,":[245],"report":[247],"our":[251,266],"implementation":[252,267],"71":[261],"Hiragana":[262],"characters,":[263],"this":[269],"on":[271],"hypercube":[273],"concurrent":[274],"computer.":[275]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}