{"id":"https://openalex.org/W2946322958","doi":"https://doi.org/10.1049/iet-its.2018.5590","title":"Fatigue driving detection model based on multi\u2010feature fusion and semi\u2010supervised active learning","display_name":"Fatigue driving detection model based on multi\u2010feature fusion and semi\u2010supervised active learning","publication_year":2019,"publication_date":"2019-05-15","ids":{"openalex":"https://openalex.org/W2946322958","doi":"https://doi.org/10.1049/iet-its.2018.5590","mag":"2946322958"},"language":"en","primary_location":{"id":"doi:10.1049/iet-its.2018.5590","doi":"https://doi.org/10.1049/iet-its.2018.5590","is_oa":false,"landing_page_url":"https://doi.org/10.1049/iet-its.2018.5590","pdf_url":null,"source":{"id":"https://openalex.org/S155689059","display_name":"IET Intelligent Transport Systems","issn_l":"1751-956X","issn":["1751-956X","1751-9578"],"is_oa":false,"is_in_doaj":true,"is_core":true,"listed_in":["ccf-c","cwts-core","doaj","dongbi-d","jufo-1","norway-1","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Intelligent Transport Systems","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"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/A5100699659","display_name":"Xu Li","orcid":"https://orcid.org/0000-0003-2772-7114","observed_orcids":["https://orcid.org/0000-0003-2772-7114","https://orcid.org/0009-0008-6293-9116"]},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xu Li","raw_affiliation_strings":["College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012932724","display_name":"Hong Lin","orcid":"https://orcid.org/0000-0003-3494-482X","observed_orcids":["https://orcid.org/0000-0003-3494-482X"]},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Hong","raw_affiliation_strings":["College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian\u2010chun Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian\u2010chun Wang","raw_affiliation_strings":["College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Transportation, Shandong University of Science and Technology, Qingdao, 266590 People's Republic of China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100408569","display_name":"Xiang Liu","orcid":"https://orcid.org/0000-0001-5763-5646","observed_orcids":["https://orcid.org/0000-0001-5763-5646"]},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Liu","raw_affiliation_strings":["School of Automotive Studies, Tongji University, Shanghai, 201804 People's Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automotive Studies, Tongji University, Shanghai, 201804 People's Republic of China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100699659"],"corresponding_institution_ids":["https://openalex.org/I80143920"],"apc_list":{"value":2790,"currency":"USD","value_usd":2790},"apc_paid":null,"fwci":7.0494,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.9678869,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"13","issue":"9","first_page":"1401","last_page":"1409"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.8306000232696533,"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/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.8306000232696533,"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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.11599999666213989,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T10370","display_name":"Traffic and Road Safety","score":0.014399999752640724,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/driver-fatigue-detection","display_name":"driver fatigue detection","score":0.9440000057220459},{"id":"https://openalex.org/keywords/semi-supervised-active-learning","display_name":"semi-supervised active learning","score":0.8679999709129333},{"id":"https://openalex.org/keywords/multi-feature-fusion","display_name":"multi-feature fusion","score":0.9860000014305115},{"id":"https://openalex.org/keywords/facial-features","display_name":"facial features","score":0.859000027179718},{"id":"https://openalex.org/keywords/driver-drowsiness","display_name":"driver drowsiness","score":0.7770000100135803},{"id":"https://openalex.org/keywords/label-propagation","display_name":"label propagation","score":0.7680000066757202},{"id":"https://openalex.org/keywords/onboard-sensors","display_name":"onboard sensors","score":0.7429999709129333}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6578638553619385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6283777952194214},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5819189548492432},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.543391227722168},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5254979729652405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5121622085571289},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.476857990026474},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44514697790145874},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13297486305236816},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1049/iet-its.2018.5590","doi":"https://doi.org/10.1049/iet-its.2018.5590","is_oa":false,"landing_page_url":"https://doi.org/10.1049/iet-its.2018.5590","pdf_url":null,"source":{"id":"https://openalex.org/S155689059","display_name":"IET Intelligent Transport Systems","issn_l":"1751-956X","issn":["1751-956X","1751-9578"],"is_oa":false,"is_in_doaj":true,"is_core":true,"listed_in":["ccf-c","cwts-core","doaj","dongbi-d","jufo-1","norway-1","poland-70","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Intelligent Transport Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4943999946117401,"id":"https://metadata.un.org/sdg/9"}],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322449","display_name":"Tongji University","ror":"https://ror.org/03rc6as71"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W22783058","https://openalex.org/W47278963","https://openalex.org/W131819148","https://openalex.org/W227339781","https://openalex.org/W1613465282","https://openalex.org/W1899217221","https://openalex.org/W1965233495","https://openalex.org/W1966149574","https://openalex.org/W1988582424","https://openalex.org/W2029772767","https://openalex.org/W2032977109","https://openalex.org/W2094726855","https://openalex.org/W2095310269","https://openalex.org/W2116646930","https://openalex.org/W2149069903","https://openalex.org/W2164752783","https://openalex.org/W2172136076","https://openalex.org/W2172717914","https://openalex.org/W2279055374","https://openalex.org/W2414309931","https://openalex.org/W2467325985","https://openalex.org/W2468367897","https://openalex.org/W2519974897","https://openalex.org/W2520542635","https://openalex.org/W2561791954","https://openalex.org/W2595203562","https://openalex.org/W2604676963","https://openalex.org/W2767520447","https://openalex.org/W2770426008","https://openalex.org/W2802132828","https://openalex.org/W2884735806","https://openalex.org/W2890770085","https://openalex.org/W2900808706"],"related_works":["https://openalex.org/W4401203615","https://openalex.org/W4402939669","https://openalex.org/W4414272017","https://openalex.org/W7103650538","https://openalex.org/W4312087186","https://openalex.org/W2947277512","https://openalex.org/W4385384871","https://openalex.org/W7164400873","https://openalex.org/W7133774112","https://openalex.org/W4320492512"],"abstract_inverted_index":{"Fatigue":[0],"driving":[1,20,34,62,75,146,176],"is":[2,42,167],"one":[3],"of":[4,8,26,32,93,100,111,129,173],"the":[5,23,69,87,90,94,97,101,107,112,136,161,165,171,174],"main":[6],"factors":[7],"traffic":[9],"accidents":[10],"and":[11,45,82,96,109,139],"there":[12],"are":[13,103,155],"many":[14],"research":[15],"efforts":[16],"focusing":[17],"on":[18,79],"fatigue":[19,61,74,145,175],"detection.":[21],"With":[22],"extensive":[24],"use":[25],"on\u2010board":[27],"sensors,":[28],"a":[29,43,72,126],"huge":[30],"number":[31,128],"unlabelled":[33],"data":[35,54,130],"can":[36,132],"be":[37,133],"easily":[38],"collected,":[39],"however,":[40],"it":[41],"costly":[44],"laborious":[46],"work":[47],"to":[48,59,105,120,135,157],"annotate":[49],"semantic":[50,122],"labels":[51,123],"for":[52,124],"these":[53,64],"manually,":[55],"posing":[56],"some":[57],"difficulties":[58],"detect":[60],"with":[63,149],"data.":[65],"In":[66,86],"this":[67],"work,":[68],"authors":[70],"propose":[71],"novel":[73],"detection":[76,147,177],"model":[77,148],"based":[78],"multi\u2010feature":[80],"fusion":[81],"semi\u2010supervised":[83],"active":[84,115],"learning.":[85],"authors\u2019":[88],"model,":[89,160],"steering":[91],"features":[92,99],"vehicle":[95],"facial":[98],"driver":[102],"fused":[104],"improve":[106],"accuracy":[108,166],"stability":[110],"model.":[113,178],"Semi\u2010supervised":[114],"learning":[116],"algorithm":[117],"allows":[118],"us":[119,141],"make":[121],"only":[125],"small":[127],"that":[131,164],"propagated":[134],"rest":[137],"data,":[138],"help":[140],"establish":[142],"an":[143],"efficient":[144],"automatic":[150],"label":[151],"propagation.":[152],"Some":[153],"experiments":[154],"conducted":[156],"validate":[158],"their":[159],"results":[162],"show":[163],"86.25%,":[168],"which":[169],"proves":[170],"effectiveness":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2019-05-29T00:00:00"}