{"id":"https://openalex.org/W4414054266","doi":"https://doi.org/10.1109/taffc.2025.3607025","title":"Brain-Machine Enhanced Intelligence for Semi-Supervised Facial Emotion Recognition","display_name":"Brain-Machine Enhanced Intelligence for Semi-Supervised Facial Emotion Recognition","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W4414054266","doi":"https://doi.org/10.1109/taffc.2025.3607025"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2025.3607025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3607025","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","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/A5101968314","display_name":"Dongjun Liu","orcid":"https://orcid.org/0000-0001-9364-9228"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongjun Liu","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9364-9228","affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042276536","display_name":"Weichen Dai","orcid":"https://orcid.org/0000-0002-5019-2755"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weichen Dai","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5019-2755","affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109636603","display_name":"Hangjie Yi","orcid":"https://orcid.org/0009-0008-1513-3793"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hangjie Yi","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-1513-3793","affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101400045","display_name":"Honggang Liu","orcid":"https://orcid.org/0009-0007-9157-6863"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honggang Liu","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-9157-6863","affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jianting Cao","orcid":"https://orcid.org/0000-0002-7749-7188"},"institutions":[{"id":"https://openalex.org/I185365093","display_name":"Saitama Institute of Technology","ror":"https://ror.org/01pkeax38","country_code":"JP","type":"education","lineage":["https://openalex.org/I185365093"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jianting Cao","raw_affiliation_strings":["Saitama Institute of Technology, Fukaya, Japan"],"raw_orcid":"https://orcid.org/0000-0002-7749-7188","affiliations":[{"raw_affiliation_string":"Saitama Institute of Technology, Fukaya, Japan","institution_ids":["https://openalex.org/I185365093"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083182987","display_name":"Qibin Zhao","orcid":"https://orcid.org/0000-0002-4442-3182"},"institutions":[{"id":"https://openalex.org/I4210126580","display_name":"RIKEN Center for Advanced Intelligence Project","ror":"https://ror.org/03ckxwf91","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210110652","https://openalex.org/I4210126580"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qibin Zhao","raw_affiliation_strings":["RIKEN Center for Advanced Intelligence Project (AIP), Chuo, Japan"],"raw_orcid":"https://orcid.org/0000-0002-4442-3182","affiliations":[{"raw_affiliation_string":"RIKEN Center for Advanced Intelligence Project (AIP), Chuo, Japan","institution_ids":["https://openalex.org/I4210126580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010366936","display_name":"Fabio Babiloni","orcid":"https://orcid.org/0000-0002-4962-176X"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Babiloni","raw_affiliation_strings":["Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0002-4962-176X","affiliations":[{"raw_affiliation_string":"Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003649465","display_name":"Wanzeng Kong","orcid":"https://orcid.org/0000-0002-0113-6968"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanzeng Kong","raw_affiliation_strings":["Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-0113-6968","affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2064881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"17","issue":"1","first_page":"119","last_page":"131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8658999800682068,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.8658999800682068,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.775600016117096,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.6241999864578247},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6103000044822693},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5496000051498413},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5379999876022339},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.48420000076293945},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.43560001254081726},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.398499995470047},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.3765999972820282}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6802999973297119},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6241999864578247},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6152999997138977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6103000044822693},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5496000051498413},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5379999876022339},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.48420000076293945},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3785000145435333},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3765999972820282},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.351500004529953},{"id":"https://openalex.org/C2779918689","wikidata":"https://www.wikidata.org/wiki/Q3771842","display_name":"Stimulus (psychology)","level":2,"score":0.3370000123977661},{"id":"https://openalex.org/C2778858076","wikidata":"https://www.wikidata.org/wiki/Q5249539","display_name":"Decodes","level":3,"score":0.33390000462532043},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3190000057220459},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.28839999437332153},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2572000026702881},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2025.3607025","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2025.3607025","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"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 Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1473009882","https://openalex.org/W1589484905","https://openalex.org/W1766934979","https://openalex.org/W1970284149","https://openalex.org/W2067583143","https://openalex.org/W2068841129","https://openalex.org/W2076807218","https://openalex.org/W2086281267","https://openalex.org/W2096733369","https://openalex.org/W2106115875","https://openalex.org/W2161402491","https://openalex.org/W2169866873","https://openalex.org/W2170883741","https://openalex.org/W2278113816","https://openalex.org/W2295107390","https://openalex.org/W2336274017","https://openalex.org/W2395579298","https://openalex.org/W2559463885","https://openalex.org/W2593768305","https://openalex.org/W2622826443","https://openalex.org/W2625929003","https://openalex.org/W2741907166","https://openalex.org/W2752788177","https://openalex.org/W2765275511","https://openalex.org/W2770645414","https://openalex.org/W2773893004","https://openalex.org/W2776446922","https://openalex.org/W2792191740","https://openalex.org/W2794908468","https://openalex.org/W2887280559","https://openalex.org/W2919115771","https://openalex.org/W2927047029","https://openalex.org/W2962804657","https://openalex.org/W2963855931","https://openalex.org/W2965382638","https://openalex.org/W2971075653","https://openalex.org/W2972996383","https://openalex.org/W2984353870","https://openalex.org/W2995255435","https://openalex.org/W2998666297","https://openalex.org/W3003218881","https://openalex.org/W3022532439","https://openalex.org/W3028543194","https://openalex.org/W3041133507","https://openalex.org/W3104123947","https://openalex.org/W3108381568","https://openalex.org/W3109620645","https://openalex.org/W3119221111","https://openalex.org/W3125345589","https://openalex.org/W3133817364","https://openalex.org/W3166542014","https://openalex.org/W3216674496","https://openalex.org/W4200114345","https://openalex.org/W4230277160","https://openalex.org/W4327663834","https://openalex.org/W4404643526"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2123478443","https://openalex.org/W2115635058","https://openalex.org/W2088830394","https://openalex.org/W2081765545","https://openalex.org/W2088050694","https://openalex.org/W3126677997","https://openalex.org/W1610857240","https://openalex.org/W2584926856","https://openalex.org/W2075935902"],"abstract_inverted_index":{"Machine":[0],"learning,":[1,4],"particularly":[2],"deep":[3],"typically":[5],"achieves":[6],"high":[7],"facial":[8,93],"emotion":[9,94],"image":[10,107,250],"recognition":[11],"accuracy":[12],"benefiting":[13],"from":[14],"multiple":[15],"labeled":[16,24,232],"data.":[17],"However,":[18],"the":[19,48,57,72,131,136,140,149,153,162,184,187,199,212,220,223],"datasets":[20,251],"usually":[21],"contain":[22,65],"insufficient":[23],"samples":[25],"and":[26,233,252],"numerous":[27],"unlabeled":[28,92,165],"data":[29,166],"since":[30],"human":[31,213],"labeling":[32,91],"is":[33,128,146,167],"a":[34,115,191],"costly":[35],"endeavor.":[36],"For":[37],"semi-supervised":[38],"learning":[39,192],"of":[40,51,121,164,222],"these":[41],"datasets,":[42],"self-training":[43],"procedure":[44],"solely":[45],"based":[46],"on":[47,159,198],"visual":[49,68,73,106,254],"features":[50],"images":[52],"fails":[53],"to":[54,71,80,113,138,248],"comprehensively":[55],"understand":[56],"intricate":[58],"high-level":[59],"semantic":[60],"features.":[61],"Since":[62],"EEG":[63,102,117,132,154,177],"signals":[64,89,103],"not":[66],"only":[67],"information":[69,78,182],"related":[70,79],"stimulus":[74],"but":[75],"also":[76],"emotional":[77],"brain":[81,122,214],"activity,":[82],"they":[83],"are":[84],"highly":[85],"suitable":[86],"as":[87,135,180],"supervisory":[88,137,181],"for":[90,183],"images.":[95,235],"In":[96],"this":[97],"study,":[98],"we":[99],"specifically":[100],"employ":[101],"evoked":[104],"by":[105,230],"stimuli":[108],"in":[109,152],"conjunction":[110],"with":[111,130],"EEGNet3D":[112],"learn":[114],"discriminative":[116],"class":[118,126,133,155,178],"representation":[119,134,156],"manifold":[120],"activity.":[123],"The":[124],"one-hot":[125],"label":[127],"replaced":[129],"train":[139],"base":[141,150,185,188],"model.":[142],"Then,":[143],"better":[144],"pseudo-labeling":[145,160],"achieved":[147],"using":[148],"model":[151,189],"manifold.":[157],"Based":[158],"results,":[161],"utilization":[163],"further":[168],"improved.":[169],"Interestingly,":[170],"our":[171,240],"findings":[172],"reveal":[173],"that":[174,194,219,239],"when":[175,202,246],"utilizing":[176],"representations":[179],"model,":[186],"demonstrates":[190],"pattern":[193],"involves":[195],"focusing":[196],"more":[197],"eye":[200],"area":[201],"making":[203],"judgments":[204],"about":[205],"emotions.":[206,216],"This":[207],"behavior":[208],"closely":[209],"resembles":[210],"how":[211],"decodes":[215],"Experiments":[217],"show":[218],"performance":[221],"proposed":[224],"method":[225,241],"can":[226],"be":[227],"effectively":[228],"enhanced":[229],"combining":[231],"pseudo-labeled":[234],"Further":[236],"experiments":[237],"demonstrate":[238],"exhibits":[242],"strong":[243],"generalization":[244],"abilities":[245],"applied":[247],"new":[249],"other":[253],"networks.":[255]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}