{"id":"https://openalex.org/W4229056557","doi":"https://doi.org/10.1145/3477314.3507268","title":"The impact of different facial expression intensities on the performance of pre-trained emotion recognition models","display_name":"The impact of different facial expression intensities on the performance of pre-trained emotion recognition models","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4229056557","doi":"https://doi.org/10.1145/3477314.3507268"},"language":"en","primary_location":{"id":"doi:10.1145/3477314.3507268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507268","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-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/A5036034810","display_name":"Hermon Faria de Araujo","orcid":null},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Hermon Faria de Araujo","raw_affiliation_strings":["Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil"],"affiliations":[{"raw_affiliation_string":"Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054257245","display_name":"F\u00e1tima L. S. Nunes","orcid":"https://orcid.org/0000-0003-0040-0752"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"F\u00e1tima L. S. Nunes","raw_affiliation_strings":["Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil"],"affiliations":[{"raw_affiliation_string":"Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil","institution_ids":["https://openalex.org/I17974374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043984374","display_name":"Ariane Machado\u2010Lima","orcid":"https://orcid.org/0000-0002-5719-338X"},"institutions":[{"id":"https://openalex.org/I17974374","display_name":"Universidade de S\u00e3o Paulo","ror":"https://ror.org/036rp1748","country_code":"BR","type":"education","lineage":["https://openalex.org/I17974374"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ariane Machado-Lima","raw_affiliation_strings":["Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil"],"affiliations":[{"raw_affiliation_string":"Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brasil","institution_ids":["https://openalex.org/I17974374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5036034810"],"corresponding_institution_ids":["https://openalex.org/I17974374"],"apc_list":null,"apc_paid":null,"fwci":0.4157,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53359684,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"41","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":1.0,"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":1.0,"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":0.9991000294685364,"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/T11448","display_name":"Face recognition and analysis","score":0.9987999796867371,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sadness","display_name":"Sadness","score":0.8805791139602661},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.8065221309661865},{"id":"https://openalex.org/keywords/disgust","display_name":"Disgust","score":0.7180203199386597},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6875503063201904},{"id":"https://openalex.org/keywords/surprise","display_name":"Surprise","score":0.6529663801193237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6061176061630249},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.4858569800853729},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4842762351036072},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.4456061124801636},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.43325328826904297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43179571628570557},{"id":"https://openalex.org/keywords/happiness","display_name":"Happiness","score":0.42820584774017334},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41408392786979675},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34392595291137695},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.1078367829322815},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1042630672454834},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.07231229543685913}],"concepts":[{"id":"https://openalex.org/C2779812673","wikidata":"https://www.wikidata.org/wiki/Q169251","display_name":"Sadness","level":3,"score":0.8805791139602661},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.8065221309661865},{"id":"https://openalex.org/C2777375102","wikidata":"https://www.wikidata.org/wiki/Q208351","display_name":"Disgust","level":3,"score":0.7180203199386597},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875503063201904},{"id":"https://openalex.org/C2780343955","wikidata":"https://www.wikidata.org/wiki/Q333173","display_name":"Surprise","level":2,"score":0.6529663801193237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6061176061630249},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.4858569800853729},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4842762351036072},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.4456061124801636},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.43325328826904297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43179571628570557},{"id":"https://openalex.org/C2778999518","wikidata":"https://www.wikidata.org/wiki/Q8","display_name":"Happiness","level":2,"score":0.42820584774017334},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41408392786979675},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34392595291137695},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.1078367829322815},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1042630672454834},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.07231229543685913},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477314.3507268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507268","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1486414894","https://openalex.org/W2001315093","https://openalex.org/W2025089570","https://openalex.org/W2045977420","https://openalex.org/W2137409775","https://openalex.org/W2161969291","https://openalex.org/W2164598857","https://openalex.org/W2297243559","https://openalex.org/W2328447414","https://openalex.org/W2341528187","https://openalex.org/W2744909235","https://openalex.org/W2775666429","https://openalex.org/W2789794973","https://openalex.org/W2806880291","https://openalex.org/W2940772629","https://openalex.org/W2947641607","https://openalex.org/W2957913628","https://openalex.org/W2980594093","https://openalex.org/W3003745987","https://openalex.org/W3007708573","https://openalex.org/W3020447069","https://openalex.org/W3101998545","https://openalex.org/W3109496323","https://openalex.org/W3117889002","https://openalex.org/W3119792370","https://openalex.org/W3158068891","https://openalex.org/W3193736813","https://openalex.org/W7064823746"],"related_works":["https://openalex.org/W4238520549","https://openalex.org/W3216173459","https://openalex.org/W2794357331","https://openalex.org/W4242611441","https://openalex.org/W4242034606","https://openalex.org/W4250499761","https://openalex.org/W2037174948","https://openalex.org/W2945121592","https://openalex.org/W1761974557","https://openalex.org/W2519456985"],"abstract_inverted_index":{"Facial":[0],"Expression":[1],"Recognition":[2],"(FER)":[3],"has":[4],"improved":[5],"a":[6,77,218],"great":[7],"deal":[8],"with":[9,81,113],"the":[10,18,31,38,41,66,95,125,200,244],"advances":[11],"of":[12,20,33,43,68,76,79,83,94,97,106,120,144,174,213,246],"machine":[13,54,133,203],"learning,":[14],"mainly":[15],"due":[16],"to":[17,30,130,168,188,209,242],"development":[19],"deep":[21],"learning":[22,51,55,134,204],"methods":[23],"for":[24,37,102,136,172,192],"automatic":[25],"facial":[26,87,103,115,146,180,214,227],"expression":[27,116,181],"classification.":[28],"Due":[29],"availability":[32],"big":[34],"datasets":[35],"required":[36],"training":[39],"processes,":[40],"amount":[42],"commercial":[44],"and":[45,52,161],"open-source":[46,99],"solutions":[47],"that":[48,199],"use":[49],"transfer":[50],"pre-trained":[53,98,132,202,232],"models":[56,70,100,135,205],"have":[57],"increased.":[58],"However,":[59],"there":[60],"is":[61],"not":[62],"enough":[63],"information":[64],"about":[65],"performance":[67,96,137,235],"these":[69],"in":[71,74,85,211,240],"non-standard":[72],"scenarios,":[73],"view":[75],"set":[78],"images":[80,112,173],"variations":[82,210],"intensity":[84,157,179,194,212],"emotional":[86],"expressions.":[88,215,228],"In":[89,216],"this":[90],"article,":[91],"an":[92],"evaluation":[93],"used":[101],"expressions":[104,147],"recognition":[105],"emotions":[107],"was":[108,223],"carried":[109],"out":[110],"on":[111],"different":[114,226],"intensities.":[117],"A":[118],"total":[119],"1512":[121],"video":[122],"frames":[123,176],"from":[124,177],"ADFES-BIV":[126,140],"dataset":[127,141],"were":[128,170,190],"submitted":[129],"five":[131],"evaluation.":[138],"The":[139,163,183,196],"contains":[142],"representations":[143],"seven":[145],"(anger,":[148],"fear,":[149],"disgust,":[150],"happiness,":[151],"neutral,":[152],"sadness,":[153],"surprise)":[154],"considering":[155],"three":[156],"levels":[158],"(low,":[159],"intermediate":[160],"high).":[162],"highest":[164],"accuracy":[165,185],"values":[166,186],"(60%":[167],"74%)":[169],"obtained":[171],"apex":[175],"high":[178],"videos.":[182],"lowest":[184],"(17%":[187],"29%)":[189],"observed":[191,224],"low":[193],"frames.":[195],"results":[197],"show":[198],"tested":[201],"are":[206],"very":[207],"susceptible":[208],"addition,":[217],"large":[219],"recall":[220],"variability":[221],"rate":[222],"among":[225],"Therefore,":[229],"before":[230],"adopting":[231],"models,":[233],"their":[234],"should":[236],"be":[237],"carefully":[238],"analyzed":[239],"order":[241],"meet":[243],"requirements":[245],"each":[247],"specific":[248],"application.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}