{"id":"https://openalex.org/W3139323134","doi":"https://doi.org/10.1109/tnnls.2022.3189996","title":"Collective Decision of One-vs-Rest Networks for Open-Set Recognition","display_name":"Collective Decision of One-vs-Rest Networks for Open-Set Recognition","publication_year":2022,"publication_date":"2022-07-14","ids":{"openalex":"https://openalex.org/W3139323134","doi":"https://doi.org/10.1109/tnnls.2022.3189996","mag":"3139323134","pmid":"https://pubmed.ncbi.nlm.nih.gov/35834456"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3189996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3189996","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.10230","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072390875","display_name":"Jaeyeon Jang","orcid":"https://orcid.org/0000-0001-6255-2044"},"institutions":[{"id":"https://openalex.org/I87111246","display_name":"Catholic University of Korea","ror":"https://ror.org/01fpnj063","country_code":"KR","type":"education","lineage":["https://openalex.org/I87111246"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaeyeon Jang","raw_affiliation_strings":["Department of Data Science, The Catholic University of Korea, Bucheon, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-6255-2044","affiliations":[{"raw_affiliation_string":"Department of Data Science, The Catholic University of Korea, Bucheon, Republic of Korea","institution_ids":["https://openalex.org/I87111246"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001540138","display_name":"Chang Ouk Kim","orcid":"https://orcid.org/0000-0002-6936-5409"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang Ouk Kim","raw_affiliation_strings":["Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-6936-5409","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Yonsei University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072390875"],"corresponding_institution_ids":["https://openalex.org/I87111246"],"apc_list":null,"apc_paid":null,"fwci":4.9943,"has_fulltext":false,"cited_by_count":45,"citation_normalized_percentile":{"value":0.95687443,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"2","first_page":"2327","last_page":"2338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9922000169754028,"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/T12676","display_name":"Machine Learning and ELM","score":0.9907000064849854,"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/softmax-function","display_name":"Softmax function","score":0.9728338718414307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7625007629394531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6365029811859131},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5827027559280396},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.5761421322822571},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.567071259021759},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5080025792121887},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5066114664077759},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4425172209739685},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4352874755859375},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42926114797592163},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3940693438053131},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06933945417404175}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9728338718414307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7625007629394531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6365029811859131},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5827027559280396},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.5761421322822571},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.567071259021759},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5080025792121887},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5066114664077759},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4425172209739685},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4352874755859375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42926114797592163},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3940693438053131},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06933945417404175},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2022.3189996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3189996","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35834456","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35834456","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 neural networks and learning systems","raw_type":null},{"id":"pmh:oai:arXiv.org:2103.10230","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.10230","pdf_url":"https://arxiv.org/pdf/2103.10230","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.10230","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.10230","pdf_url":"https://arxiv.org/pdf/2103.10230","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.800000011920929,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G5138209366","display_name":null,"funder_award_id":"NRF-2019R1A2B5B01070358","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W572355794","https://openalex.org/W967544008","https://openalex.org/W1032927584","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1917989004","https://openalex.org/W2001610032","https://openalex.org/W2007339694","https://openalex.org/W2018459374","https://openalex.org/W2088965486","https://openalex.org/W2100332042","https://openalex.org/W2100717508","https://openalex.org/W2117539524","https://openalex.org/W2119880843","https://openalex.org/W2147062276","https://openalex.org/W2163605009","https://openalex.org/W2182396527","https://openalex.org/W2194321275","https://openalex.org/W2194775991","https://openalex.org/W2248269543","https://openalex.org/W2325939864","https://openalex.org/W2466114631","https://openalex.org/W2526075485","https://openalex.org/W2604589052","https://openalex.org/W2734358244","https://openalex.org/W2735411683","https://openalex.org/W2756388459","https://openalex.org/W2783398758","https://openalex.org/W2895752198","https://openalex.org/W2898307578","https://openalex.org/W2901114541","https://openalex.org/W2904509905","https://openalex.org/W2921187422","https://openalex.org/W2962835968","https://openalex.org/W2963026800","https://openalex.org/W2963149653","https://openalex.org/W2963875483","https://openalex.org/W2963924212","https://openalex.org/W2965989958","https://openalex.org/W2973218493","https://openalex.org/W2982857584","https://openalex.org/W3011147549","https://openalex.org/W3016045843","https://openalex.org/W3016494398","https://openalex.org/W3033765509","https://openalex.org/W3035081753","https://openalex.org/W3046193700","https://openalex.org/W3083641663","https://openalex.org/W3099936844","https://openalex.org/W3102616566","https://openalex.org/W3113047382","https://openalex.org/W3115571254","https://openalex.org/W3134961575","https://openalex.org/W3177034761","https://openalex.org/W3189623384","https://openalex.org/W3198636227","https://openalex.org/W4214671648","https://openalex.org/W4288418813","https://openalex.org/W4289021499","https://openalex.org/W6625168331","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6740957146","https://openalex.org/W6745891213","https://openalex.org/W6754995574","https://openalex.org/W6760009982","https://openalex.org/W6776216542"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W2980176872","https://openalex.org/W2899027234","https://openalex.org/W4300326282","https://openalex.org/W2742395793","https://openalex.org/W3141979996","https://openalex.org/W3113054633","https://openalex.org/W2810018382"],"abstract_inverted_index":{"Unknown":[0],"examples":[1,26],"that":[2,77,83,97,139,146,159,201],"are":[3,58,147],"unseen":[4],"during":[5],"training":[6],"often":[7],"appear":[8],"in":[9,114,151],"real-world":[10],"pattern":[11],"recognition":[12,32],"tasks,":[13],"and":[14,27,41,93,196],"an":[15,131],"intelligent":[16],"self-learning":[17],"system":[18],"should":[19],"be":[20,88,163],"able":[21],"to":[22,60,142,155,186],"distinguish":[23],"between":[24],"known":[25,168],"unknown":[28,156,160],"examples.":[29],"Accordingly,":[30],"open-set":[31],"(OSR),":[33],"which":[34,115],"addresses":[35],"the":[36,81,84,152,171,179,184,197,202,209],"problem":[37],"of":[38],"classifying":[39],"knowns":[40],"identifying":[42],"unknowns,":[43],"has":[44],"recently":[45],"been":[46],"highlighted.":[47],"However,":[48],"conventional":[49],"deep":[50],"neural":[51,123,137],"networks":[52,118],"(DNNs)":[53],"using":[54],"a":[55,73,110,121,134],"softmax":[56,153],"layer":[57,154],"vulnerable":[59],"overgeneralization,":[61],"producing":[62],"high":[63],"confidence":[64,144],"scores":[65,145],"for":[66,105],"unknowns.":[67],"In":[68],"this":[69,108],"article,":[70],"we":[71],"propose":[72],"simple":[74,135],"OSR":[75,85],"method":[76,204],"is":[78,128,133,140,175,218],"based":[79],"on":[80,193],"intuition":[82],"performance":[86,104],"can":[87,162],"maximized":[89],"by":[90,177,183,212],"setting":[91],"strict":[92],"sophisticated":[94],"decision":[95,173],"boundaries":[96],"reject":[98],"unknowns":[99],"while":[100],"maintaining":[101],"satisfactory":[102],"classification":[103],"knowns.":[106],"For":[107],"purpose,":[109],"novel":[111],"network":[112,124,138],"structure,":[113],"multiple":[116,180],"one-vs-rest":[117],"(OVRNs)":[119],"follow":[120],"convolutional":[122],"(CNN)":[125],"feature":[126],"extractor,":[127],"proposed.":[129],"Here,":[130],"OVRN":[132],"feedforward":[136],"designed":[141],"assign":[143],"lower":[148],"than":[149,208],"those":[150],"samples":[157,161],"so":[158],"more":[164],"effectively":[165,213],"separated":[166],"from":[167],"classes.":[169],"Furthermore,":[170],"collective":[172],"score":[174],"modeled":[176],"combining":[178],"decisions":[181],"reached":[182],"OVRNs":[185],"alleviate":[187],"overgeneralization.":[188,215],"Extensive":[189],"experiments":[190],"were":[191],"conducted":[192],"various":[194],"datasets,":[195],"experimental":[198],"results":[199],"show":[200],"proposed":[203],"performs":[205],"significantly":[206],"better":[207],"state-of-the-art":[210],"methods":[211],"reducing":[214],"The":[216],"code":[217],"available":[219],"at":[220],"https://github.com/JaeyeonJang/Openset-collective-decision.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
