{"id":"https://openalex.org/W3164215669","doi":"https://doi.org/10.1145/3441250.3441263","title":"A Transfer Learning Approach to Compound Facial Expression Recognition","display_name":"A Transfer Learning Approach to Compound Facial Expression Recognition","publication_year":2020,"publication_date":"2020-11-13","ids":{"openalex":"https://openalex.org/W3164215669","doi":"https://doi.org/10.1145/3441250.3441263","mag":"3164215669"},"language":"en","primary_location":{"id":"doi:10.1145/3441250.3441263","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3441250.3441263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 4th International Conference on Advances in Image Processing","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/A5090052670","display_name":"Yuanlun Xie","orcid":"https://orcid.org/0000-0001-9682-2065"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanlun Xie","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001104882","display_name":"Wenhong Tian","orcid":"https://orcid.org/0000-0002-5551-9796"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhong Tian","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087928662","display_name":"Tingsong Ma","orcid":"https://orcid.org/0000-0001-7874-6126"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingsong Ma","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"95","last_page":"101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9979000091552734,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7476053237915039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6949748992919922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6945798993110657},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6863094568252563},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.6643193960189819},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6374057531356812},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.6015039682388306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5444371700286865},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5406133532524109},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.44521528482437134},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42648929357528687},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39679405093193054},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07766598463058472}],"concepts":[{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7476053237915039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6949748992919922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6945798993110657},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6863094568252563},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.6643193960189819},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6374057531356812},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.6015039682388306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5444371700286865},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5406133532524109},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.44521528482437134},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42648929357528687},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39679405093193054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07766598463058472},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3441250.3441263","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3441250.3441263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 4th International Conference on Advances in Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1964762821","https://openalex.org/W1980331490","https://openalex.org/W2014185685","https://openalex.org/W2065379720","https://openalex.org/W2139916508","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2506506742","https://openalex.org/W2600389231","https://openalex.org/W2612719531","https://openalex.org/W2745497104","https://openalex.org/W2750692136","https://openalex.org/W2798583514","https://openalex.org/W2800170478","https://openalex.org/W2805502563","https://openalex.org/W2900431199","https://openalex.org/W2902200737","https://openalex.org/W2908186737","https://openalex.org/W2924180817","https://openalex.org/W2963712289","https://openalex.org/W3122081138","https://openalex.org/W4239072543","https://openalex.org/W4247092244","https://openalex.org/W4250294168","https://openalex.org/W4253378646","https://openalex.org/W4289710724","https://openalex.org/W4297683907","https://openalex.org/W4403242122","https://openalex.org/W6750843368"],"related_works":["https://openalex.org/W2642127892","https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W4323520705","https://openalex.org/W2356663679","https://openalex.org/W2169777806","https://openalex.org/W3027190010"],"abstract_inverted_index":{"Recent":[0],"advanced":[1],"research":[2,42],"shows":[3],"that":[4,130],"deep":[5,27,107,136],"learning":[6,28,81,137,151],"has":[7,40],"great":[8,41],"potential":[9],"in":[10,15,142],"facial":[11,36,70,110,124,162],"expression":[12,18,71,85,163],"recognition,":[13,86],"specially,":[14],"the":[16,113,120,123,134,149,154],"basic":[17],"recognition":[19,164],"field,":[20],"many":[21],"researchers":[22],"have":[23],"proposed":[24],"lots":[25],"of":[26,62,109,122],"networks":[29],"with":[30,94],"excellent":[31],"performance.":[32],"As":[33,144],"for":[34,83],"compound":[35,69,84,161],"expression,":[37,111],"although":[38],"it":[39],"value,":[43],"there":[44,57],"are":[45],"only":[46],"few":[47],"researches":[48],"existed,":[49],"and":[50,112],"their":[51],"performance":[52],"is":[53,58,103,116,153],"not":[54],"satisfactory.":[55],"So,":[56],"still":[59],"a":[60,79,90,95],"lot":[61],"work":[63],"to":[64,67,105,118,157,160],"be":[65,158],"done":[66],"improve":[68],"recognition.":[72],"To":[73],"address":[74],"this":[75],"problem,":[76],"we":[77,88,147],"introduce":[78],"transfer":[80,150],"solution":[82],"where":[87],"design":[89],"fine-tuning":[91,114],"structure":[92],"combining":[93],"VGG-19":[96,100],"pre-trained":[97,101],"network.":[98],"The":[99,126],"network":[102,115],"used":[104,117],"extract":[106],"features":[108],"obtain":[119],"category":[121],"expression.":[125],"experimental":[127],"results":[128],"show":[129],"our":[131],"approach":[132,152],"improves":[133],"state-of-the-art":[135],"method":[138],"by":[139],"about":[140],"5.31%":[141],"accuracy.":[143],"far":[145],"as":[146],"know,":[148],"first":[155],"time":[156],"applied":[159],"based":[165],"on":[166],"CFEE":[167],"dataset.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
