{"id":"https://openalex.org/W4388667110","doi":"https://doi.org/10.1109/bhi58575.2023.10313521","title":"Accurate Identification of Human Emotional States from Images Using Deep Learning","display_name":"Accurate Identification of Human Emotional States from Images Using Deep Learning","publication_year":2023,"publication_date":"2023-10-15","ids":{"openalex":"https://openalex.org/W4388667110","doi":"https://doi.org/10.1109/bhi58575.2023.10313521"},"language":"en","primary_location":{"id":"doi:10.1109/bhi58575.2023.10313521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi58575.2023.10313521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-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/A5108308837","display_name":"E. Sung Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Emmy Yang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5058469124","display_name":"Jake Y. Chen","orcid":"https://orcid.org/0000-0001-8829-7504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jake Y. Chen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5108308837"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.262,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61077145,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.8906320333480835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7303330898284912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7195162773132324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.611893892288208},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5877894163131714},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5431494116783142},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.542726457118988},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5352853536605835},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.4702911376953125},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4677080512046814},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46742552518844604},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4669533669948578},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44970107078552246},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4466196298599243},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44456666707992554},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42706558108329773},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4251117408275604},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3595227003097534},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34108057618141174},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08259791135787964}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.8906320333480835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7303330898284912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7195162773132324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.611893892288208},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5877894163131714},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5431494116783142},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.542726457118988},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5352853536605835},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.4702911376953125},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4677080512046814},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46742552518844604},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4669533669948578},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44970107078552246},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4466196298599243},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44456666707992554},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42706558108329773},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4251117408275604},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3595227003097534},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34108057618141174},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08259791135787964},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/bhi58575.2023.10313521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bhi58575.2023.10313521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W64154658","https://openalex.org/W1978262206","https://openalex.org/W2041616772","https://openalex.org/W2097822100","https://openalex.org/W2106115875","https://openalex.org/W2106390385","https://openalex.org/W2125127226","https://openalex.org/W2140351517","https://openalex.org/W2194775991","https://openalex.org/W2268421884","https://openalex.org/W2282529734","https://openalex.org/W2335087342","https://openalex.org/W2556844902","https://openalex.org/W2795620863","https://openalex.org/W2798536775","https://openalex.org/W2963460857","https://openalex.org/W3036526054","https://openalex.org/W3094644839","https://openalex.org/W3100513545","https://openalex.org/W3189322178","https://openalex.org/W3212708089","https://openalex.org/W4225319377","https://openalex.org/W4236533540","https://openalex.org/W4236965008","https://openalex.org/W4250722239","https://openalex.org/W6780140667"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W1968481813","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W4243161226"],"abstract_inverted_index":{"Facial":[0],"expression":[1],"recognition":[2,17],"is":[3,74],"a":[4,19,83,87],"crucial":[5],"aspect":[6],"of":[7,93,123,150,152,175],"human":[8],"communication,":[9],"especially":[10],"for":[11,160],"building":[12],"social":[13],"relationships.":[14],"However,":[15],"machine-based":[16],"remains":[18],"challenging":[20],"task":[21],"where":[22],"implemented":[23],"SOTA":[24],"methods":[25,126],"achieved":[26,114],"testing":[27],"accuracies":[28],"from":[29,76],"50%":[30],"to":[31,85,168],"60%":[32],"on":[33,127],"FER-2013.":[34],"Our":[35,110],"research":[36],"proposes":[37],"an":[38],"automatic":[39],"emotion":[40,176],"identification":[41],"system":[42,59],"that":[43,122],"utilizes":[44],"emotional":[45,153,161,185],"state":[46,162,186],"heatmaps":[47,163],"(ES-MAPs)":[48],"and":[49,64,80,105,148,164,173,190],"neural":[50],"network":[51],"classification":[52],"algorithms.":[53],"Using":[54],"MediaPipe":[55],"Face":[56],"Mesh,":[57],"our":[58],"extracts":[60],"facial":[61,140],"landmark":[62,78],"coordinates":[63],"calculates":[65],"the":[66,77,128,138,146,158,171],"distance":[67],"between":[68],"all":[69],"landmarks.":[70],"A":[71],"neutral":[72],"baseline":[73],"subtracted":[75],"distances":[79],"saved":[81],"as":[82],"heatmap":[84],"train":[86],"designed":[88],"CNN":[89],"model.":[90],"The":[91],"use":[92],"ES-MAPs":[94,133],"minimizes":[95],"noise":[96],"introduced":[97],"by":[98],"significant":[99,143],"variation":[100,106],"in":[101,107,116,145,182,187],"image":[102],"lighting":[103],"conditions":[104],"head":[108],"rotation.":[109],"proposed":[111],"system,":[112],"ESH-Net,":[113],"75%":[115],"test":[117],"accuracy,":[118],"15%":[119],"greater":[120],"than":[121,137],"other":[124],"state-of-the-art":[125],"HDFE":[129],"dataset.":[130],"In":[131],"addition,":[132],"produced":[134],"better":[135],"clustering":[136],"original":[139],"images,":[141],"indicating":[142],"improvement":[144],"separability":[147],"consistency":[149],"representation":[151],"states.":[154],"This":[155],"study":[156],"demonstrates":[157],"potential":[159],"deep":[165],"learning":[166],"models":[167],"significantly":[169],"improve":[170],"accuracy":[172],"efficiency":[174],"identification,":[177],"which":[178],"can":[179],"greatly":[180],"assist":[181],"assessing":[183],"patient\u2019s":[184],"medical":[188],"diagnosis":[189],"practice.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}