{"id":"https://openalex.org/W4408281487","doi":"https://doi.org/10.1109/iecon55916.2024.10905539","title":"Facial Expression Recognition via Closed-Loop Transcription","display_name":"Facial Expression Recognition via Closed-Loop Transcription","publication_year":2024,"publication_date":"2024-11-03","ids":{"openalex":"https://openalex.org/W4408281487","doi":"https://doi.org/10.1109/iecon55916.2024.10905539"},"language":"en","primary_location":{"id":"doi:10.1109/iecon55916.2024.10905539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon55916.2024.10905539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100362341","display_name":"Xuan Liu","orcid":"https://orcid.org/0000-0002-9331-6543"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Liu","raw_affiliation_strings":["Harbin Institute of Technology,Department of Control Science and Engineering,Harbin,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Department of Control Science and Engineering,Harbin,PR China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101585094","display_name":"Jiachen Ma","orcid":"https://orcid.org/0000-0002-0110-7438"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiachen Ma","raw_affiliation_strings":["Harbin Institute of Technology,Department of Control Science and Engineering,Weihai,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Department of Control Science and Engineering,Weihai,PR China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100367066","display_name":"Qiang Wang","orcid":"https://orcid.org/0000-0003-2715-0255"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Wang","raw_affiliation_strings":["Harbin Institute of Technology,Department of Control Science and Engineering,Harbin,PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology,Department of Control Science and Engineering,Harbin,PR China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7491999864578247,"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":0.7491999864578247,"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/facial-expression-recognition","display_name":"Facial expression recognition","score":0.5953117609024048},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5735083818435669},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.556885838508606},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.5011820793151855},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4771275520324707},{"id":"https://openalex.org/keywords/closed-loop","display_name":"Closed loop","score":0.44250500202178955},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43187806010246277},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35752788186073303},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.33598947525024414},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3225562274456024},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13166910409927368},{"id":"https://openalex.org/keywords/control-engineering","display_name":"Control engineering","score":0.12664100527763367}],"concepts":[{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.5953117609024048},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5735083818435669},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.556885838508606},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.5011820793151855},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4771275520324707},{"id":"https://openalex.org/C3019251811","wikidata":"https://www.wikidata.org/wiki/Q5135346","display_name":"Closed loop","level":2,"score":0.44250500202178955},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43187806010246277},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35752788186073303},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.33598947525024414},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3225562274456024},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13166910409927368},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.12664100527763367},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon55916.2024.10905539","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon55916.2024.10905539","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":16,"referenced_works":["https://openalex.org/W2070353225","https://openalex.org/W2115941714","https://openalex.org/W2164931791","https://openalex.org/W2253728219","https://openalex.org/W2963391470","https://openalex.org/W2964337551","https://openalex.org/W2974043081","https://openalex.org/W2981626792","https://openalex.org/W3065974826","https://openalex.org/W3157999215","https://openalex.org/W3161346624","https://openalex.org/W4220862273","https://openalex.org/W4221135977","https://openalex.org/W4389474546","https://openalex.org/W6683994600","https://openalex.org/W6780322082"],"related_works":["https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W2162992774","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2901126000","https://openalex.org/W4323520705","https://openalex.org/W2116055069","https://openalex.org/W2356663679","https://openalex.org/W3027190010"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"are":[4,32,82,216],"the":[5,14,30,39,64,68,126,130,134,137,145,149,154,173,178,191,198,206,210,214,232,242],"most":[6],"widely":[7],"used":[8],"and":[9,36,55,73,119,129,151,175,209,222],"successful":[10],"approaches":[11],"for":[12,109,163,177,197],"accomplishing":[13],"Facial":[15],"Expression":[16],"Recognition":[17],"(FER)":[18],"task.":[19],"However,":[20],"these":[21],"technologies":[22],"appear":[23],"to":[24,53,62,95,102,218,241],"have":[25],"reached":[26],"a":[27,77,104,168,182],"bottleneck":[28],"since":[29],"networks":[31],"becoming":[33],"increasingly":[34],"complex":[35,223],"heavier,":[37],"yet":[38],"performance":[40,212],"improvements":[41],"remain":[42],"minimal.":[43],"The":[44,157,187,202],"\"black":[45],"box\"":[46],"nature":[47],"of":[48,70,116,136,147,153,205,213,220,227],"CNNs":[49],"makes":[50],"it":[51],"challenging":[52],"identify":[54],"address":[56,63],"this":[57],"crux.":[58],"This":[59,113],"paper":[60],"aims":[61],"issue":[65],"by":[66,235],"utilizing":[67],"principles":[69],"data":[71,123,127,165],"compression":[72],"discriminative":[74],"representation":[75,180],"within":[76],"plausible":[78],"theoretical":[79],"framework.":[80],"We":[81],"employing":[83],"an":[84,97,117],"innovative":[85],"computational":[86],"framework,":[87],"drawing":[88],"inspiration":[89],"from":[90],"feedback":[91,141],"loop":[92],"control":[93],"systems,":[94],"develop":[96],"interpretable":[98],"closed-loop":[99,200],"transcription":[100,138,155],"model":[101],"generate":[103],"Linear":[105],"Discriminative":[106],"Representation":[107],"(LDR)":[108],"multi-class":[110],"real-world":[111],"datasets.":[112],"model,":[114],"comprised":[115],"encoder":[118,174,215],"decoder":[120,176,208],"that":[121],"facilitates":[122],"mapping":[124],"between":[125,172],"space":[128],"feature":[131],"space,":[132],"employs":[133],"output":[135],"system":[139],"as":[140],"or":[142],"guidance,":[143],"with":[144],"objective":[146],"improving":[148],"accuracy":[150,226],"efficiency":[152],"process.":[156],"optimal":[158],"LDR":[159],"is":[160],"learned":[161,179,207,243],"jointly":[162],"all":[164],"classes":[166],"through":[167],"two-player":[169],"minimax":[170],"game":[171],"over":[181],"single":[183],"rate":[184],"reduction-based":[185],"objective.":[186],"studies":[188],"conducted":[189],"on":[190,231],"FER2013":[192,233],"dataset":[193,234],"show":[194],"promising":[195],"results":[196],"proposed":[199],"formulation.":[201],"visual":[203],"quality":[204],"classification":[211],"comparable":[217],"those":[219],"large":[221],"networks.":[224],"An":[225],"70.97%":[228],"was":[229],"attained":[230],"applying":[236],"Principal":[237],"Component":[238],"Analysis":[239],"(PCA)":[240],"representation.":[244]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
