{"id":"https://openalex.org/W4402167562","doi":"https://doi.org/10.1109/tfuzz.2024.3454069","title":"A Fuzzy Neural Network Enabled Deep Subspace Domain Adaptive Fusion Approaches for Facial Expression Recognition","display_name":"A Fuzzy Neural Network Enabled Deep Subspace Domain Adaptive Fusion Approaches for Facial Expression Recognition","publication_year":2024,"publication_date":"2024-09-03","ids":{"openalex":"https://openalex.org/W4402167562","doi":"https://doi.org/10.1109/tfuzz.2024.3454069"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2024.3454069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3454069","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":"https://openalex.org/A5008286525","display_name":"Wanneng Shu","orcid":"https://orcid.org/0000-0002-8589-2241"},"institutions":[{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wanneng Shu","raw_affiliation_strings":["College of Computer Science, South-Central Minzu University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, South-Central Minzu University, Wuhan, China","institution_ids":["https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007204465","display_name":"Feng Zhang","orcid":"https://orcid.org/0000-0003-4943-7898"},"institutions":[{"id":"https://openalex.org/I4210161995","display_name":"Yulin University","ror":"https://ror.org/05rp1t554","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210161995"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Zhang","raw_affiliation_strings":["School of Information Engineering, Yulin University, Yulin, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Yulin University, Yulin, China","institution_ids":["https://openalex.org/I4210161995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019779939","display_name":"Runze Wan","orcid":"https://orcid.org/0000-0003-2536-6001"},"institutions":[{"id":"https://openalex.org/I4210111616","display_name":"Wuhan Business University","ror":"https://ror.org/0282ggx30","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210111616"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runze Wan","raw_affiliation_strings":["School of Information Engineering, Wuhan Business University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Wuhan Business University, Wuhan, China","institution_ids":["https://openalex.org/I4210111616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008286525"],"corresponding_institution_ids":["https://openalex.org/I145897649"],"apc_list":null,"apc_paid":null,"fwci":1.3121,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81631484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"33","issue":"1","first_page":"392","last_page":"405"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.880299985408783,"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/T10057","display_name":"Face and Expression Recognition","score":0.880299985408783,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.8726999759674072,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6500985622406006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5944176912307739},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5903433561325073},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5875442624092102},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5757046937942505},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5041033029556274},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.46256670355796814},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.44793522357940674},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.42350879311561584},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4075482487678528}],"concepts":[{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6500985622406006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5944176912307739},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5903433561325073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5875442624092102},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5757046937942505},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5041033029556274},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.46256670355796814},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.44793522357940674},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.42350879311561584},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4075482487678528}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2024.3454069","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3454069","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":[],"awards":[{"id":"https://openalex.org/G894963094","display_name":null,"funder_award_id":"62373382","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2900164843","https://openalex.org/W2980175391","https://openalex.org/W3041607159","https://openalex.org/W3043030071","https://openalex.org/W3056251842","https://openalex.org/W3081006209","https://openalex.org/W3093895707","https://openalex.org/W3094014349","https://openalex.org/W3127817797","https://openalex.org/W3151571129","https://openalex.org/W3154457442","https://openalex.org/W3156060522","https://openalex.org/W3158022345","https://openalex.org/W3163585031","https://openalex.org/W3163747707","https://openalex.org/W3167583064","https://openalex.org/W3177390112","https://openalex.org/W3188959449","https://openalex.org/W3200588317","https://openalex.org/W3205068595","https://openalex.org/W3211154457","https://openalex.org/W3217596337","https://openalex.org/W4205166102","https://openalex.org/W4210729356","https://openalex.org/W4210984325","https://openalex.org/W4220968645","https://openalex.org/W4226157726","https://openalex.org/W4285095938","https://openalex.org/W4285250231","https://openalex.org/W4296558638","https://openalex.org/W4385789665","https://openalex.org/W4391720077"],"related_works":["https://openalex.org/W200201533","https://openalex.org/W4171918","https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W2162992774","https://openalex.org/W4323520705","https://openalex.org/W2356663679"],"abstract_inverted_index":{"There":[0],"are":[1,10],"many":[2],"interference":[3],"factors":[4],"in":[5,23,112,158],"the":[6,30,52,57,66,95,113,120,127,142,163],"real":[7],"world":[8],"that":[9,141],"not":[11],"related":[12],"to":[13,28,101,107,125],"facial":[14,33,155],"expressions,":[15],"such":[16],"as":[17],"background,":[18],"lighting":[19],"intensity,":[20],"and":[21,90,151,161,166],"changes":[22],"image":[24],"resolution.":[25],"In":[26],"order":[27],"address":[29],"problem":[31],"of":[32,70,77,85,105,133],"expression":[34,156],"recognition,":[35],"this":[36],"article":[37],"proposes":[38],"a":[39,75,83,109],"fuzzy":[40,53,62,143],"neural":[41,144],"network":[42,59,145],"enabled":[43],"deep":[44,71],"subspace":[45],"domain":[46],"adaptive":[47],"fusion":[48],"(FNN-DSDAF)":[49],"by":[50],"integrating":[51],"logic":[54,63],"module":[55,64],"into":[56],"convolutional":[58],"structure.":[60],"The":[61,137],"integrates":[65],"powerful":[67],"learning":[68],"ability":[69,150],"networks":[72],"can":[73],"learn":[74],"set":[76],"robust":[78],"Gaussian":[79,87],"membership":[80,88],"functions":[81,89],"through":[82],"series":[84],"learnable":[86],"logical":[91],"operations.":[92],"When":[93],"training":[94],"classical":[96],"normalized":[97],"exponential":[98],"loss":[99,123],"function":[100,124],"force":[102],"different":[103],"categories":[104],"samples":[106,134],"maintain":[108],"certain":[110],"distance":[111],"learned":[114],"feature":[115,148],"space,":[116],"FNN-DSDAF":[117],"further":[118],"uses":[119],"local":[121,128],"hold":[122],"make":[126],"clusters":[129],"within":[130],"each":[131],"category":[132],"more":[135],"compact.":[136],"experimental":[138],"results":[139],"demonstrated":[140],"had":[146],"good":[147],"decoupling":[149],"was":[152],"suitable":[153],"for":[154],"understanding":[157],"real-world":[159],"scenarios,":[160],"improve":[162],"accuracy,":[164],"reliability,":[165],"robustness.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}