{"id":"https://openalex.org/W7108201854","doi":"https://doi.org/10.1109/tfuzz.2025.3593951","title":"Fuzzy Membership-Driven Adaptive Sample Mining for Facial Expression Recognition","display_name":"Fuzzy Membership-Driven Adaptive Sample Mining for Facial Expression Recognition","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W7108201854","doi":"https://doi.org/10.1109/tfuzz.2025.3593951"},"language":null,"primary_location":{"id":"doi:10.1109/tfuzz.2025.3593951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3593951","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","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":null,"display_name":"Xuxiong Liu","orcid":"https://orcid.org/0009-0001-6882-9021"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuxiong Liu","raw_affiliation_strings":["Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0001-6882-9021","affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liuwei An","orcid":"https://orcid.org/0009-0008-6729-3545"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liuwei An","raw_affiliation_strings":["Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0008-6729-3545","affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kang Shen","orcid":"https://orcid.org/0009-0003-9010-2819"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Shen","raw_affiliation_strings":["Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0003-9010-2819","affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ziyang Zhang","orcid":"https://orcid.org/0009-0009-7160-5772"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Zhang","raw_affiliation_strings":["Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0009-7160-5772","affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiao Sun","orcid":"https://orcid.org/0000-0001-9750-7032"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Sun","raw_affiliation_strings":["Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-9750-7032","affiliations":[{"raw_affiliation_string":"Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machines, School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54716017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":"12","first_page":"4240","last_page":"4251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7989000082015991,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7989000082015991,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.09290000051259995,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.019999999552965164,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6177999973297119},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5665000081062317},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.4984999895095825},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4853000044822693},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.45579999685287476},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4271000027656555},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4027999937534332},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.349700003862381},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.3402000069618225}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6276999711990356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6177999973297119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6116999983787537},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5665000081062317},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.4984999895095825},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4853000044822693},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.45579999685287476},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4271000027656555},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4027999937534332},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.384799987077713},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3659999966621399},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C2780049643","wikidata":"https://www.wikidata.org/wiki/Q5511139","display_name":"Fuzzy rule","level":4,"score":0.3370000123977661},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.3021000027656555},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.2849999964237213},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.25699999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2025.3593951","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3593951","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6890088319778442,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G796335958","display_name":null,"funder_award_id":"62441614","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":45,"referenced_works":["https://openalex.org/W43927268","https://openalex.org/W1980331490","https://openalex.org/W2037603696","https://openalex.org/W2041616772","https://openalex.org/W2048679005","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2481681431","https://openalex.org/W2620998106","https://openalex.org/W2738672149","https://openalex.org/W2745497104","https://openalex.org/W2887842788","https://openalex.org/W2904483377","https://openalex.org/W2948606739","https://openalex.org/W2954821120","https://openalex.org/W2964274690","https://openalex.org/W2964292098","https://openalex.org/W2967052791","https://openalex.org/W3003720578","https://openalex.org/W3034185248","https://openalex.org/W3035336958","https://openalex.org/W3091476632","https://openalex.org/W3118361021","https://openalex.org/W3118530108","https://openalex.org/W3126991911","https://openalex.org/W3172678098","https://openalex.org/W3173787706","https://openalex.org/W3179103990","https://openalex.org/W4206411193","https://openalex.org/W4226368482","https://openalex.org/W4287947470","https://openalex.org/W4304086144","https://openalex.org/W4312465353","https://openalex.org/W4312823769","https://openalex.org/W4313128368","https://openalex.org/W4313132476","https://openalex.org/W4313171337","https://openalex.org/W4313555039","https://openalex.org/W4319300140","https://openalex.org/W4385731896","https://openalex.org/W4390166461","https://openalex.org/W4390168417","https://openalex.org/W4402167562","https://openalex.org/W4403690225","https://openalex.org/W4408241989"],"related_works":[],"abstract_inverted_index":{"Facial":[0],"expression":[1,28],"recognition":[2,24],"(FER)":[3],"datasets":[4],"are":[5,68],"plagued":[6],"by":[7],"fuzzy":[8,48,87,226],"label":[9],"uncertainty":[10],"due":[11],"to":[12,103,140,155,230],"interclass":[13],"similarities,":[14],"compound":[15],"emotions,":[16],"and":[17,77,159,186,196,206,216],"annotation":[18],"subjectivity.":[19],"Moreover,":[20],"the":[21,62,85,107,111,119,130,142,147,160,173,183,221,235],"complexity":[22],"of":[23,65,144,234],"differs":[25],"across":[26],"various":[27],"categories,":[29],"making":[30],"an":[31,164,240],"undifferentiated":[32],"method":[33,211],"inequitable":[34],"for":[35,126],"each":[36],"expression.":[37],"In":[38,91],"this":[39],"work,":[40],"we":[41],"propose":[42],"adaptive":[43],"sample":[44],"mining":[45],"(ASM),":[46],"a":[47,56,95,136,151],"membership-driven":[49],"framework":[50],"with":[51],"two":[52],"innovations:":[53],"it":[54,73,93,170,228],"constructs":[55],"category-specific":[57],"dynamic":[58],"threshold":[59],"set":[60],"as":[61,84],"average":[63],"probabilities":[64],"samples":[66,83,105],"that":[67,169,209],"correctly":[69],"predicted,":[70],"through":[71],"which":[72],"explicitly":[74],"separates":[75],"clean":[76,108,131],"noisy":[78,161,176,201,217],"subsets":[79],"while":[80],"leaving":[81],"ambiguous":[82,112,148,215],"intermediate":[86],"region":[88,100],"between":[89],"them.":[90],"addition,":[92],"introduces":[94],"rule":[96],"based":[97,224],"on":[98,182,194,198,225],"multilocal":[99],"prediction":[101],"consistency":[102],"reclassify":[104],"from":[106,175],"subset":[109,113,132,149,162],"into":[110],"when":[114],"local":[115],"predictions":[116],"conflict.":[117],"Finally,":[118],"triregularization":[120],"module":[121],"implements":[122],"tailored":[123],"training":[124],"approaches":[125],"these":[127],"three":[128],"subsets:":[129],"is":[133],"trained":[134],"using":[135],"supervised":[137],"learning":[138,153,166],"strategy":[139,154],"maximize":[141],"utility":[143],"high-quality":[145],"annotations,":[146],"adopts":[150],"mutual":[152],"enhance":[156],"discrimination":[157],"capability,":[158],"employs":[163],"unsupervised":[165],"technique":[167],"so":[168],"can":[171,212],"minimize":[172],"influence":[174],"labels.":[177,218,236],"We":[178],"performed":[179],"comprehensive":[180],"experiments":[181],"RAF-DB,":[184],"FERPlus,":[185],"AffectNet.":[187],"The":[188,203],"proposed":[189],"ASM":[190],"achieved":[191],"90.94%":[192],"accuracy":[193],"RAF-DB":[195],"86.81%":[197],"its":[199],"synthetic":[200],"version.":[202],"ablation":[204],"experiment":[205],"analysis":[207],"demonstrate":[208],"our":[210],"efficiently":[213],"identify":[214],"By":[219],"weighting":[220],"classification":[222],"loss":[223],"membership,":[227],"helps":[229],"make":[231],"efficient":[232],"use":[233],"This":[237],"results":[238],"in":[239,242],"improvement":[241],"accuracy.":[243]},"counts_by_year":[],"updated_date":"2025-12-03T23:09:05.601824","created_date":"2025-12-03T00:00:00"}