{"id":"https://openalex.org/W4400275554","doi":"https://doi.org/10.1109/access.2024.3422383","title":"A Multimodal Driver Anger Recognition Method Based on Context-Awareness","display_name":"A Multimodal Driver Anger Recognition Method Based on Context-Awareness","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400275554","doi":"https://doi.org/10.1109/access.2024.3422383"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3422383","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3422383","pdf_url":null,"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":"http://dx.doi.org/10.1109/access.2024.3422383","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076195394","display_name":"Tongqiang Ding","orcid":"https://orcid.org/0000-0002-2212-961X"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongqiang Ding","raw_affiliation_strings":["Transportation College, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-2212-961X","affiliations":[{"raw_affiliation_string":"Transportation College, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069630739","display_name":"Kexin Zhang","orcid":"https://orcid.org/0000-0001-8950-2178"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kexin Zhang","raw_affiliation_strings":["Transportation College, Jilin University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transportation College, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101662320","display_name":"Shuai Gao","orcid":"https://orcid.org/0009-0001-0695-7183"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuai Gao","raw_affiliation_strings":["Jilin Communications Polytechnic, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jilin Communications Polytechnic, Changchun, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108951209","display_name":"Xinning Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinning Miao","raw_affiliation_strings":["Beijing Jingwei Hirain Technologies Company Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jingwei Hirain Technologies Company Inc., Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051598995","display_name":"Jianfeng Xi","orcid":"https://orcid.org/0000-0002-4488-0850"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Xi","raw_affiliation_strings":["Transportation College, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-4488-0850","affiliations":[{"raw_affiliation_string":"Transportation College, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.546,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.82812895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"12","issue":null,"first_page":"118533","last_page":"118550"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9968000054359436,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9860000014305115,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7671834826469421},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.617156445980072},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6087641716003418},{"id":"https://openalex.org/keywords/situation-awareness","display_name":"Situation awareness","score":0.5581748485565186},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5459732413291931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5143481492996216},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5042010545730591},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.47292807698249817},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4685341417789459},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.4639793038368225},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42013949155807495},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38519465923309326},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11032336950302124},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08299356698989868}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7671834826469421},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.617156445980072},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6087641716003418},{"id":"https://openalex.org/C145804949","wikidata":"https://www.wikidata.org/wiki/Q478123","display_name":"Situation awareness","level":2,"score":0.5581748485565186},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5459732413291931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5143481492996216},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5042010545730591},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.47292807698249817},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4685341417789459},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.4639793038368225},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42013949155807495},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38519465923309326},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11032336950302124},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08299356698989868},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3422383","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3422383","pdf_url":null,"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:0c6aafec794a436bb18b0f7624992b0c","is_oa":true,"landing_page_url":"https://doaj.org/article/0c6aafec794a436bb18b0f7624992b0c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 12, Pp 118533-118550 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3422383","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/access.2024.3422383","pdf_url":null,"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/5","display_name":"Gender equality","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1588539311","https://openalex.org/W1766486746","https://openalex.org/W1973087318","https://openalex.org/W1976725440","https://openalex.org/W1978445814","https://openalex.org/W2000820603","https://openalex.org/W2004804300","https://openalex.org/W2030315268","https://openalex.org/W2035372623","https://openalex.org/W2039051707","https://openalex.org/W2056980486","https://openalex.org/W2060211611","https://openalex.org/W2076905378","https://openalex.org/W2087618018","https://openalex.org/W2144264893","https://openalex.org/W2161969291","https://openalex.org/W2180587936","https://openalex.org/W2253728219","https://openalex.org/W2331098876","https://openalex.org/W2372355899","https://openalex.org/W2474922233","https://openalex.org/W2506506742","https://openalex.org/W2547040949","https://openalex.org/W2566621105","https://openalex.org/W2588299441","https://openalex.org/W2745497104","https://openalex.org/W2902499931","https://openalex.org/W2909296529","https://openalex.org/W2910165986","https://openalex.org/W2914650326","https://openalex.org/W2951935310","https://openalex.org/W2971977515","https://openalex.org/W2980587061","https://openalex.org/W3016378313","https://openalex.org/W3044867770","https://openalex.org/W3089365109","https://openalex.org/W3109961563","https://openalex.org/W3122081138","https://openalex.org/W3135221627","https://openalex.org/W4229022325","https://openalex.org/W4300459376","https://openalex.org/W4308630605","https://openalex.org/W4321019606","https://openalex.org/W4386822700","https://openalex.org/W4387454353","https://openalex.org/W4387993155","https://openalex.org/W4388574325","https://openalex.org/W6732602522","https://openalex.org/W6784185043"],"related_works":["https://openalex.org/W2531159956","https://openalex.org/W2158625435","https://openalex.org/W1968844886","https://openalex.org/W2030507284","https://openalex.org/W2386052819","https://openalex.org/W3105646692","https://openalex.org/W4387914125","https://openalex.org/W2584926856","https://openalex.org/W2075935902","https://openalex.org/W2014713986"],"abstract_inverted_index":{"In":[0],"today\u2019s":[1],"society,":[2],"the":[3,15,24,51,75,139],"harm":[4],"of":[5,17,26,154],"driving":[6,72,79,117],"anger":[7,44,110],"to":[8,49,77,107],"traffic":[9],"safety":[10],"is":[11],"increasingly":[12],"prominent.":[13],"With":[14],"development":[16],"human-computer":[18],"interaction":[19],"and":[20,74,102,116,151,156,165],"intelligent":[21],"transportation":[22],"systems,":[23],"application":[25],"biometric":[27],"technology":[28],"in":[29,55,67,144],"driver":[30,43],"emotion":[31,45,57,111,145,162,167],"recognition":[32,46,58,112,163,168],"has":[33],"attracted":[34],"widespread":[35],"attention.":[36],"This":[37],"study":[38],"proposes":[39],"a":[40],"context-aware":[41],"multi-modal":[42,56,109,132,161],"method":[47,87,141],"(CA-MDER)":[48],"address":[50],"main":[52],"issues":[53],"encountered":[54],"tasks.":[59],"These":[60],"include":[61],"individual":[62],"differences":[63],"among":[64],"drivers,":[65],"variability":[66],"emotional":[68],"expression":[69],"across":[70],"different":[71],"scenarios,":[73],"inability":[76],"capture":[78],"behavior":[80],"information":[81],"that":[82,138],"represents":[83],"vehicle-to-vehicle":[84],"interaction.":[85],"The":[86,135],"employs":[88],"Attention":[89],"Mechanism-Depthwise":[90],"Separable":[91],"Convolutional":[92],"Neural":[93],"Networks":[94],"(AM-DSCNN),":[95],"an":[96,149],"improved":[97],"Support":[98],"Vector":[99],"Machines":[100],"(SVM),":[101],"Random":[103],"Forest":[104],"(RF)":[105],"models":[106],"perform":[108],"using":[113],"facial,":[114],"vocal,":[115],"state":[118],"information.":[119],"It":[120],"also":[121],"uses":[122],"Context-Aware":[123],"Reinforcement":[124],"Learning":[125],"(CA-RL)":[126],"based":[127],"adaptive":[128],"weight":[129],"distribution":[130],"for":[131],"decision-level":[133],"fusion.":[134],"results":[136],"show":[137],"proposed":[140],"performs":[142],"well":[143],"classification":[146],"metrics,":[147],"with":[148],"accuracy":[150],"F1":[152],"score":[153],"91.68%":[155],"90.37%,":[157],"respectively,":[158],"demonstrating":[159],"robust":[160],"performance":[164],"powerful":[166],"capabilities.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
