{"id":"https://openalex.org/W4389459490","doi":"https://doi.org/10.1109/mits.2023.3333882","title":"DERNet: Driver Emotion Recognition Using Onboard Camera","display_name":"DERNet: Driver Emotion Recognition Using Onboard Camera","publication_year":2023,"publication_date":"2023-12-07","ids":{"openalex":"https://openalex.org/W4389459490","doi":"https://doi.org/10.1109/mits.2023.3333882"},"language":"en","primary_location":{"id":"doi:10.1109/mits.2023.3333882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3333882","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","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/A5017472722","display_name":"Dingyu Wang","orcid":"https://orcid.org/0000-0003-4870-777X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingyu Wang","raw_affiliation_strings":["Department of Automation, BNRIST, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRIST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046933572","display_name":"Shaocheng Jia","orcid":"https://orcid.org/0000-0001-9586-5151"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Shaocheng Jia","raw_affiliation_strings":["Department of Civil Engineering, The University of Hong Kong, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-9586-5151","affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, The University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100636075","display_name":"Xin Pei","orcid":"https://orcid.org/0000-0003-3807-2264"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Pei","raw_affiliation_strings":["Department of Automation, BNRIST, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRIST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031038629","display_name":"Chunyang Han","orcid":"https://orcid.org/0000-0001-9876-8824"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunyang Han","raw_affiliation_strings":["Department of Automation, BNRIST, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Automation, BNRIST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081663090","display_name":"Danya Yao","orcid":"https://orcid.org/0000-0001-5032-6322"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danya Yao","raw_affiliation_strings":["Department of Automation, BNRIST, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5032-6322","affiliations":[{"raw_affiliation_string":"Department of Automation, BNRIST, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101691929","display_name":"Dezhi Liu","orcid":"https://orcid.org/0000-0001-6053-1493"},"institutions":[{"id":"https://openalex.org/I4210100528","display_name":"ENN (China)","ror":"https://ror.org/018a8yy17","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210100528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dezhi Liu","raw_affiliation_strings":["ENN Energy Logistics, Langfang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ENN Energy Logistics, Langfang, China","institution_ids":["https://openalex.org/I4210100528"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3947,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.89204467,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"16","issue":"2","first_page":"117","last_page":"132"},"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/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9987000226974487,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9955000281333923,"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/benchmark","display_name":"Benchmark (surveying)","score":0.8581575155258179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6817188858985901},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5556911826133728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46289578080177307},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4576415717601776},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.43754255771636963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4369387626647949}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.8581575155258179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6817188858985901},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5556911826133728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46289578080177307},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4576415717601776},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.43754255771636963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4369387626647949},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mits.2023.3333882","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mits.2023.3333882","pdf_url":null,"source":{"id":"https://openalex.org/S131000621","display_name":"IEEE Intelligent Transportation Systems Magazine","issn_l":"1939-1390","issn":["1939-1390","1941-1197"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Transportation Systems Magazine","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8208538107","display_name":null,"funder_award_id":"2021YFC3001500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W173805407","https://openalex.org/W234798790","https://openalex.org/W1522301498","https://openalex.org/W1970884985","https://openalex.org/W1979743748","https://openalex.org/W1991129058","https://openalex.org/W2027867692","https://openalex.org/W2047030012","https://openalex.org/W2056591378","https://openalex.org/W2060678323","https://openalex.org/W2064675550","https://openalex.org/W2073669264","https://openalex.org/W2081835714","https://openalex.org/W2097290407","https://openalex.org/W2109572311","https://openalex.org/W2117866167","https://openalex.org/W2136000821","https://openalex.org/W2137410597","https://openalex.org/W2139916508","https://openalex.org/W2152826865","https://openalex.org/W2164623278","https://openalex.org/W2164809575","https://openalex.org/W2194775991","https://openalex.org/W2198512331","https://openalex.org/W2201235005","https://openalex.org/W2263218431","https://openalex.org/W2277498883","https://openalex.org/W2298865080","https://openalex.org/W2520623877","https://openalex.org/W2548529926","https://openalex.org/W2556844902","https://openalex.org/W2560081062","https://openalex.org/W2586008137","https://openalex.org/W2604258616","https://openalex.org/W2769950277","https://openalex.org/W2802427277","https://openalex.org/W2808614768","https://openalex.org/W2885976210","https://openalex.org/W2889870770","https://openalex.org/W2902298447","https://openalex.org/W2945192711","https://openalex.org/W2963112684","https://openalex.org/W2963182155","https://openalex.org/W3006912862","https://openalex.org/W3012546716","https://openalex.org/W3042183479","https://openalex.org/W3044030936","https://openalex.org/W3048524731","https://openalex.org/W3093198960","https://openalex.org/W3128704584","https://openalex.org/W3130358931","https://openalex.org/W3132295368","https://openalex.org/W3135221627","https://openalex.org/W3136617080","https://openalex.org/W3137028092","https://openalex.org/W3137500711","https://openalex.org/W3153847062","https://openalex.org/W3188183700","https://openalex.org/W3208016204","https://openalex.org/W4206139378","https://openalex.org/W4226455208","https://openalex.org/W4255938156","https://openalex.org/W4309630093","https://openalex.org/W4312465353","https://openalex.org/W4312619736","https://openalex.org/W4366765095","https://openalex.org/W4377286928","https://openalex.org/W6631190155","https://openalex.org/W6634664584","https://openalex.org/W6635634533","https://openalex.org/W6766978945","https://openalex.org/W6781194548","https://openalex.org/W6792139870"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"Driver":[0],"emotion":[1,57,71,78,121,154],"is":[2,44,124,144,169],"considered":[3],"an":[4,25,70],"essential":[5],"factor":[6],"associated":[7],"with":[8],"driving":[9],"behaviors":[10],"and":[11,17,89,97,112,202,218,226],"thus":[12],"influences":[13],"traffic":[14],"safety.":[15],"Dynamically":[16],"accurately":[18],"recognizing":[19],"the":[20,36,53,76,92,117,132,135,148,160,178,183,186,199,215,221],"emotions":[21],"of":[22,38,47,55,85,102,150,185,197,220],"drivers":[23,37],"plays":[24],"important":[26],"role":[27],"in":[28,210],"road":[29],"safety,":[30],"especially":[31,60],"for":[32,61,131,153,164],"professional":[33],"drivers,":[34],"e.g.,":[35],"passenger":[39],"service":[40],"vehicles.":[41],"However,":[42],"there":[43],"a":[45,48,119,128,137,166,203,211],"lack":[46],"benchmark":[49,73],"to":[50,108,126,146,190,206],"quantitatively":[51],"evaluate":[52],"performance":[54,168],"driver":[56,77,120,139],"recognition":[58,72,122,155],"performance,":[59],"various":[62,109],"application":[63,110,196],"situations.":[64],"In":[65],"this":[66],"article,":[67],"we":[68],"propose":[69],"based":[74],"on":[75,91,172,177],"facial":[79],"expression":[80],"(DEFE)":[81],"dataset,":[82],"which":[83],"consists":[84],"two":[86,105],"splits:":[87],"training":[88],"testing":[90],"same":[93],"set":[94],"(split":[95,100],"1)":[96],"different":[98,157],"sets":[99],"2)":[101],"drivers.":[103,158],"These":[104],"splits":[106,228],"correspond":[107],"scenarios":[111],"have":[113],"diverse":[114],"challenges.":[115],"For":[116,134],"former,":[118],"network":[123],"proposed":[125,145,187,200,222],"provide":[127],"competitive":[129],"baseline":[130],"benchmark.":[133],"latter,":[136],"novel":[138],"representation":[140],"difference":[141],"minimization":[142],"loss":[143],"enhance":[147],"learning":[149],"common":[151],"representations":[152],"over":[156],"Moreover,":[159],"minimum":[161],"required":[162],"information":[163],"achieving":[165],"satisfactory":[167],"also":[170],"explored":[171],"split":[173],"2.":[174],"Comprehensive":[175],"experiments":[176],"DEFE":[179],"dataset":[180,227],"clearly":[181],"demonstrate":[182],"superiority":[184],"methods":[188,201],"compared":[189],"other":[191],"state-of-the-art":[192],"methods.":[193,223],"An":[194],"example":[195],"applying":[198],"voting":[204],"mechanism":[205],"real-world":[207],"data":[208],"collected":[209],"naturalistic":[212],"environment":[213],"reveals":[214],"strong":[216],"practicality":[217],"readiness":[219],"The":[224],"codes":[225],"are":[229],"publicly":[230],"available":[231],"at":[232],"<uri":[233],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[234],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/wdy806/CDERNet/</uri>":[235],".":[236]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}