{"id":"https://openalex.org/W3096970626","doi":"https://doi.org/10.1108/ijicc-07-2020-0088","title":"Facial expression recognition based on bidirectional gated recurrent units within deep residual network","display_name":"Facial expression recognition based on bidirectional gated recurrent units within deep residual network","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3096970626","doi":"https://doi.org/10.1108/ijicc-07-2020-0088","mag":"3096970626"},"language":"en","primary_location":{"id":"doi:10.1108/ijicc-07-2020-0088","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-07-2020-0088","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","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/A5009223452","display_name":"Wenjuan Shen","orcid":"https://orcid.org/0000-0002-6193-825X"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjuan Shen","raw_affiliation_strings":["Gongqing College of Nanchang University, Gongqingcheng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gongqing College of Nanchang University, Gongqingcheng, China","institution_ids":["https://openalex.org/I141649914"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018106725","display_name":"Xiaoling Li","orcid":"https://orcid.org/0000-0002-1489-117X"},"institutions":[{"id":"https://openalex.org/I141649914","display_name":"Nanchang University","ror":"https://ror.org/042v6xz23","country_code":"CN","type":"education","lineage":["https://openalex.org/I141649914"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoling Li","raw_affiliation_strings":["Gongqing College of Nanchang University, Gongqingcheng, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gongqing College of Nanchang University, Gongqingcheng, China","institution_ids":["https://openalex.org/I141649914"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141649914"],"apc_list":null,"apc_paid":null,"fwci":1.2048,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.8053929,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"13","issue":"4","first_page":"527","last_page":"543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9987999796867371,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.8595903515815735},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8042945265769958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6404540538787842},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5748945474624634},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.5247958898544312},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4952963888645172},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4686526656150818},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4497862756252289},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44396647810935974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3967175781726837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8595903515815735},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8042945265769958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6404540538787842},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5748945474624634},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.5247958898544312},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4952963888645172},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4686526656150818},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4497862756252289},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44396647810935974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3967175781726837},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijicc-07-2020-0088","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijicc-07-2020-0088","pdf_url":null,"source":{"id":"https://openalex.org/S124503262","display_name":"International Journal of Intelligent Computing and Cybernetics","issn_l":"1756-378X","issn":["1756-378X","1756-3798"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Computing and Cybernetics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1689711448","https://openalex.org/W2035372623","https://openalex.org/W2103943262","https://openalex.org/W2134860945","https://openalex.org/W2194775991","https://openalex.org/W2198512331","https://openalex.org/W2217426128","https://openalex.org/W2274287116","https://openalex.org/W2277498883","https://openalex.org/W2281407413","https://openalex.org/W2297337743","https://openalex.org/W2341528187","https://openalex.org/W2345305417","https://openalex.org/W2490049321","https://openalex.org/W2500329338","https://openalex.org/W2515770085","https://openalex.org/W2517304597","https://openalex.org/W2531409750","https://openalex.org/W2548529926","https://openalex.org/W2560935139","https://openalex.org/W2580662672","https://openalex.org/W2760073239","https://openalex.org/W2760398086","https://openalex.org/W2768859775","https://openalex.org/W2906690643","https://openalex.org/W3003566194","https://openalex.org/W3101998545"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W2922073769","https://openalex.org/W4378510483","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378505373","https://openalex.org/W2642127892"],"abstract_inverted_index":{"Purpose":[0],"recent":[1],"years,":[2],"facial":[3,114,158,208],"expression":[4,115,159],"recognition":[5,116,169,181,192,212,216],"has":[6,98,190],"been":[7],"widely":[8],"used":[9],"in":[10,194,229],"human":[11],"machine":[12],"interaction,":[13],"clinical":[14],"medicine":[15],"and":[16,64,148,164,167,171,214],"safe":[17],"driving.":[18],"However,":[19],"there":[20],"is":[21,71,103,141,154,183],"a":[22,50,112,195],"limitation":[23],"that":[24,187],"conventional":[25],"recurrent":[26,57],"neural":[27],"networks":[28,59],"can":[29],"only":[30],"learn":[31],"the":[32,65,76,83,86,90,138,145,151,168,176,188,201,205,210],"time-series":[33],"characteristics":[34],"of":[35,67,78,85,162,207],"expressions":[36],"based":[37,53],"on":[38,54,156],"one-way":[39],"propagation":[40],"information.":[41],"Design/methodology/approach":[42],"To":[43],"solve":[44],"such":[45],"limitation,":[46],"this":[47],"paper":[48,110],"proposes":[49,111],"novel":[51,113],"model":[52,93,117,140,153,203],"bidirectional":[55],"gated":[56],"unit":[58],"(Bi-GRUs)":[60],"with":[61,133,175,218],"two-way":[62],"propagations,":[63],"theory":[66],"identity":[68],"mapping":[69],"residuals":[70],"adopted":[72],"to":[73,105,118,123,128,143,224],"effectively":[74],"prevent":[75],"problem":[77],"gradient":[79],"disappearance":[80],"caused":[81],"by":[82],"depth":[84],"introduced":[87],"network.":[88],"Since":[89],"Inception-V3":[91],"network":[92,132],"for":[94,204],"spatial":[95],"feature":[96],"extraction":[97],"too":[99],"many":[100],"parameters,":[101,125],"it":[102],"prone":[104],"overfitting":[106],"during":[107],"training.":[108],"This":[109],"add":[119],"two":[120,157],"reduction":[121],"modules":[122],"reduce":[124],"so":[126],"as":[127],"obtain":[129],"an":[130],"Inception-W":[131],"better":[134],"generalization.":[135],"Findings":[136],"Finally,":[137],"proposed":[139,202],"pretrained":[142,152],"determine":[144],"best":[146],"settings":[147],"selections.":[149],"Then,":[150],"experimented":[155],"data":[160],"sets":[161],"CK+":[163],"Oulu-":[165],"CASIA,":[166],"performance":[170],"efficiency":[172],"are":[173],"compared":[174],"existing":[177],"methods.":[178],"The":[179],"highest":[180],"rate":[182],"99.6%,":[184],"which":[185],"shows":[186],"method":[189],"good":[191],"accuracy":[193,213],"certain":[196],"range.":[197],"Originality/value":[198],"By":[199],"using":[200],"applications":[206,228],"expression,":[209],"high":[211],"robust":[215],"results":[217],"lower":[219],"time":[220],"consumption":[221],"will":[222],"help":[223],"build":[225],"more":[226],"sophisticated":[227],"real":[230],"world.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
