{"id":"https://openalex.org/W3019849343","doi":"https://doi.org/10.1109/lsp.2020.2989670","title":"Accurate and Reliable Facial Expression Recognition Using Advanced Softmax Loss With Fixed Weights","display_name":"Accurate and Reliable Facial Expression Recognition Using Advanced Softmax Loss With Fixed Weights","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3019849343","doi":"https://doi.org/10.1109/lsp.2020.2989670","mag":"3019849343"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.2989670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2989670","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5100703115","display_name":"Ping Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"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":true,"raw_author_name":"Ping Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi\u2019an, China","School of Information Engineering, Yulin University, Yulin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Information Engineering, Yulin University, Yulin, China","institution_ids":["https://openalex.org/I4210161995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412406","display_name":"Gang Liu","orcid":"https://orcid.org/0000-0001-9491-744X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Liu","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi\u2019an, China","School of Computer Science & Technology Xidian University Xi'an China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Computer Science & Technology Xidian University Xi'an China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418247","display_name":"Quan Wang","orcid":"https://orcid.org/0000-0001-6913-8604"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quan Wang","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi\u2019an, China","School of Computer Science & Technology Xidian University Xi'an China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Computer Science & Technology Xidian University Xi'an China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026243783","display_name":"Jiang Wu","orcid":"https://orcid.org/0000-0002-6548-9551"},"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":"Jiang Wu","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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100703115"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I4210161995"],"apc_list":null,"apc_paid":null,"fwci":2.6715,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.89810473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"27","issue":null,"first_page":"725","last_page":"729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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":0.9976999759674072,"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/softmax-function","display_name":"Softmax function","score":0.9566004276275635},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7720398902893066},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6794334053993225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6461637020111084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5877808928489685},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5509693026542664},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5057599544525146},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4918968677520752},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4622490406036377},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.455194354057312},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.428152859210968},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.35443854331970215}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9566004276275635},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7720398902893066},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6794334053993225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6461637020111084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5877808928489685},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5509693026542664},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5057599544525146},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4918968677520752},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4622490406036377},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.455194354057312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.428152859210968},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.35443854331970215},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.2989670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.2989670","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1166193582","display_name":null,"funder_award_id":"61972302","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3927331725","display_name":null,"funder_award_id":"61702395","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4608637678","display_name":null,"funder_award_id":"61711530248","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":39,"referenced_works":["https://openalex.org/W44815768","https://openalex.org/W1677182931","https://openalex.org/W1983793001","https://openalex.org/W2041616772","https://openalex.org/W2052041602","https://openalex.org/W2079678116","https://openalex.org/W2095809036","https://openalex.org/W2097415784","https://openalex.org/W2102605133","https://openalex.org/W2115941714","https://openalex.org/W2194775991","https://openalex.org/W2474193198","https://openalex.org/W2520774990","https://openalex.org/W2551403050","https://openalex.org/W2609575245","https://openalex.org/W2738672149","https://openalex.org/W2744909235","https://openalex.org/W2784294927","https://openalex.org/W2798553619","https://openalex.org/W2799041689","https://openalex.org/W2805080735","https://openalex.org/W2805613995","https://openalex.org/W2889978276","https://openalex.org/W2902916789","https://openalex.org/W2908694412","https://openalex.org/W2910883248","https://openalex.org/W2940983946","https://openalex.org/W2961224374","https://openalex.org/W2962898354","https://openalex.org/W2963466847","https://openalex.org/W2963712289","https://openalex.org/W2969985801","https://openalex.org/W3009883635","https://openalex.org/W3035336958","https://openalex.org/W3101227480","https://openalex.org/W6726946684","https://openalex.org/W6750843368","https://openalex.org/W6761654431","https://openalex.org/W6891715281"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4226420367","https://openalex.org/W2980176872","https://openalex.org/W3095152779","https://openalex.org/W3119773509","https://openalex.org/W3128220219","https://openalex.org/W3006353185","https://openalex.org/W2947839263","https://openalex.org/W3120400911"],"abstract_inverted_index":{"An":[0],"important":[1],"challenge":[2],"for":[3],"facial":[4],"expression":[5,31],"recognition":[6],"(FER)":[7],"is":[8,55,62,140],"that":[9,138,151],"real-world":[10,132],"training":[11],"data":[12,88],"are":[13],"usually":[14],"imbalanced.":[15],"Although":[16],"many":[17,147],"deep":[18,30,124],"learning":[19],"approaches":[20,149],"have":[21,41],"been":[22],"proposed":[23,97,116],"to":[24,82,108],"enhance":[25,109],"the":[26,44,60,84,101,105,129],"discriminative":[27,110],"power":[28,111],"of":[29],"features":[32],"and":[33,90,94,131,144,150,160],"enable":[34],"a":[35],"good":[36],"predictive":[37],"effect,":[38],"few":[39],"works":[40],"focused":[42],"on":[43,128],"multiclass":[45],"imbalance":[46,89],"problem.":[47],"When":[48],"supervised":[49],"by":[50,87],"softmax":[51,79],"loss":[52,80,117],"(SL),":[53],"which":[54],"widely":[56],"used":[57],"in":[58,104,112,122],"FER,":[59],"classifier":[61],"often":[63],"biased":[64],"against":[65],"minority":[66],"categories":[67],"(i.e.,":[68],"smaller":[69],"interclass":[70,102],"angular":[71,106],"distances).":[72],"In":[73],"this":[74],"letter,":[75],"we":[76],"present":[77],"advanced":[78],"(ASL)":[81],"mitigate":[83],"bias":[85],"induced":[86],"hence":[91],"increase":[92],"accuracy":[93],"reliability.":[95],"The":[96,115],"ASL":[98,139],"essentially":[99],"magnifies":[100],"diversity":[103],"space":[107],"every":[113],"category.":[114],"can":[118,153],"easily":[119,154],"be":[120,155],"implemented":[121],"any":[123],"network.":[125],"Extensive":[126],"experiments":[127],"FER2013":[130],"affective":[133],"faces":[134],"(RAF)":[135],"databases":[136],"demonstrate":[137],"significantly":[141],"more":[142],"accurate":[143],"reliable":[145],"than":[146],"state-of-the-art":[148],"it":[152],"plugged":[156],"into":[157],"other":[158],"methods":[159],"improves":[161],"their":[162],"performance.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}