{"id":"https://openalex.org/W2997263156","doi":"https://doi.org/10.1109/access.2020.2963913","title":"Multiple Attention Network for Facial Expression Recognition","display_name":"Multiple Attention Network for Facial Expression Recognition","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2997263156","doi":"https://doi.org/10.1109/access.2020.2963913","mag":"2997263156"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2963913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2963913","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08949474.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08949474.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101591421","display_name":"Yanling Gan","orcid":"https://orcid.org/0000-0002-6803-590X"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanling Gan","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001864927","display_name":"Jingying Chen","orcid":"https://orcid.org/0000-0002-1523-3478"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingying Chen","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101726016","display_name":"Zongkai Yang","orcid":"https://orcid.org/0000-0001-8354-721X"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongkai Yang","raw_affiliation_strings":["National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103106171","display_name":"Luhui Xu","orcid":"https://orcid.org/0000-0002-8201-8380"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luhui Xu","raw_affiliation_strings":["Department of Computer Science, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101591421"],"corresponding_institution_ids":["https://openalex.org/I40963666"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.2739,"has_fulltext":true,"cited_by_count":85,"citation_normalized_percentile":{"value":0.98796577,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"7383","last_page":"7393"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9980999827384949,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/discriminative-model","display_name":"Discriminative model","score":0.8946548700332642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8131427764892578},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.7739837169647217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6623141765594482},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6368938088417053},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5211127400398254},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.48546960949897766},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48421812057495117},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.4705539047718048},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4462762475013733},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4409901797771454},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36290791630744934},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.3026464581489563}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8946548700332642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8131427764892578},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.7739837169647217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6623141765594482},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6368938088417053},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5211127400398254},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.48546960949897766},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48421812057495117},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.4705539047718048},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4462762475013733},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4409901797771454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36290791630744934},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.3026464581489563},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2963913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2963913","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08949474.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3db54066b52e4d779bb0b49177c1d462","is_oa":true,"landing_page_url":"https://doaj.org/article/3db54066b52e4d779bb0b49177c1d462","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 7383-7393 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2963913","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2963913","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08949474.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1408900520","display_name":null,"funder_award_id":"2019AEA170","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G1954675122","display_name":null,"funder_award_id":"61977027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2301403321","display_name":null,"funder_award_id":"61772380","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2884910486","display_name":null,"funder_award_id":"Technology","funder_id":"https://openalex.org/F4320322724","funder_display_name":"Ministry of Education, India"},{"id":"https://openalex.org/G3294234326","display_name":null,"funder_award_id":"2018YFB1004","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G3435950671","display_name":null,"funder_award_id":"and Gr","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4581004536","display_name":null,"funder_award_id":"2019AAA044","funder_id":"https://openalex.org/F4320335792","funder_display_name":"Hubei Technological Innovation Special Fund"},{"id":"https://openalex.org/G5300120560","display_name":null,"funder_award_id":"2017CFA007","funder_id":"https://openalex.org/F4320327654","funder_display_name":"Foundation for Innovative Research Groups of Hubei Province of China"},{"id":"https://openalex.org/G6300186070","display_name":null,"funder_award_id":"2018YFB1004504","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8460048242","display_name":null,"funder_award_id":"2019AEA170","funder_id":"https://openalex.org/F4320327928","funder_display_name":"Major Technology Innovation of Hubei Province"},{"id":"https://openalex.org/G8525944409","display_name":null,"funder_award_id":"2019AEA170","funder_id":"https://openalex.org/F4320335792","funder_display_name":"Hubei Technological Innovation Special Fund"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322724","display_name":"Ministry of Education, India","ror":"https://ror.org/048xjjh50"},{"id":"https://openalex.org/F4320323173","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21"},{"id":"https://openalex.org/F4320327654","display_name":"Foundation for Innovative Research Groups of Hubei Province of China","ror":null},{"id":"https://openalex.org/F4320327928","display_name":"Major Technology Innovation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335792","display_name":"Hubei Technological Innovation Special Fund","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2997263156.pdf","grobid_xml":"https://content.openalex.org/works/W2997263156.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W253816493","https://openalex.org/W1520861770","https://openalex.org/W1968015059","https://openalex.org/W2014185685","https://openalex.org/W2088575594","https://openalex.org/W2103943262","https://openalex.org/W2115941714","https://openalex.org/W2117866167","https://openalex.org/W2134860945","https://openalex.org/W2217426128","https://openalex.org/W2244142460","https://openalex.org/W2293804193","https://openalex.org/W2325939864","https://openalex.org/W2490049321","https://openalex.org/W2730601341","https://openalex.org/W2737398044","https://openalex.org/W2738672149","https://openalex.org/W2750692136","https://openalex.org/W2752782242","https://openalex.org/W2773003563","https://openalex.org/W2782522780","https://openalex.org/W2793980118","https://openalex.org/W2798583514","https://openalex.org/W2798775284","https://openalex.org/W2884048435","https://openalex.org/W2891628231","https://openalex.org/W2894217452","https://openalex.org/W2902598059","https://openalex.org/W2911384653","https://openalex.org/W2914907652","https://openalex.org/W2962858109","https://openalex.org/W2962926870","https://openalex.org/W2963420686","https://openalex.org/W2963495494","https://openalex.org/W2963712289","https://openalex.org/W4297791193","https://openalex.org/W6609788658","https://openalex.org/W6631082944","https://openalex.org/W6672481139","https://openalex.org/W6723215617","https://openalex.org/W6753257457","https://openalex.org/W6755106128"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W4256502920","https://openalex.org/W103652678","https://openalex.org/W2999756192","https://openalex.org/W4226090359","https://openalex.org/W3112714922","https://openalex.org/W2985118265","https://openalex.org/W2952602176"],"abstract_inverted_index":{"One":[0],"key":[1],"challenge":[2],"in":[3,94],"facial":[4,16],"expression":[5,54,79],"recognition":[6,36,55,80],"(FER)":[7],"is":[8],"the":[9,58,95,98,105,109,132,138,150,153,171],"extraction":[10],"of":[11,19,122,135,152],"discriminative":[12,25,91],"features":[13],"from":[14,108],"critical":[15,71,155],"regions.":[17,156],"Because":[18],"their":[20],"promising":[21],"ability":[22],"to":[23,33,52],"learn":[24],"features,":[26],"visual":[27,50],"attention":[28,44,51,86,103,117],"mechanisms":[29],"are":[30,174],"increasingly":[31],"used":[32],"address":[34],"pattern":[35],"problems.":[37],"This":[38],"paper":[39],"presents":[40],"a":[41,61,84,115,120,143],"novel":[42],"multiple":[43,85],"network":[45],"that":[46,147,182],"simulates":[47],"humans'":[48],"coarse-to-fine":[49,74],"improve":[53],"performance.":[56],"In":[57],"proposed":[59],"network,":[60],"region-aware":[62],"sub-net":[63,81],"(RASnet)":[64],"learns":[65,89,149],"binary":[66],"masks":[67,107],"for":[68],"locating":[69],"expression-related":[70],"regions":[72],"with":[73,83,119],"granularity":[75],"levels":[76],"and":[77,168,170,176],"an":[78],"(ERSnet)":[82],"(MA)":[87],"block":[88,100,113,140],"comprehensive":[90],"features.":[92],"Embedded":[93],"convolutional":[96],"layers,":[97],"MA":[99,112,139],"fuses":[101],"diversified":[102,136],"using":[104],"learned":[106],"RASnet.":[110],"The":[111,179],"contains":[114],"hybrid":[116],"branch":[118,146],"series":[121],"sub-branches,":[123],"where":[124],"each":[125],"sub-branch":[126],"provides":[127],"region-specific":[128],"attention.":[129],"To":[130],"explore":[131],"complementary":[133],"benefits":[134],"attention,":[137],"also":[141],"has":[142],"weight":[144],"learning":[145],"adaptively":[148],"contributions":[151],"different":[154],"Experiments":[157],"have":[158],"been":[159],"carried":[160],"out":[161],"on":[162],"two":[163],"publicly":[164],"available":[165],"databases,":[166],"RAF":[167],"CK+,":[169],"reported":[172],"accuracies":[173],"85.69%":[175],"96.28%,":[177],"respectively.":[178],"results":[180],"indicate":[181],"our":[183],"method":[184],"achieves":[185],"competitive":[186],"or":[187],"better":[188],"performance":[189],"than":[190],"state-of-the-art":[191],"methods.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":21},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}