{"id":"https://openalex.org/W4220778421","doi":"https://doi.org/10.1142/s0218213022500245","title":"Driver Fatigue Detection Using Improved Deep Learning and Personalized Framework","display_name":"Driver Fatigue Detection Using Improved Deep Learning and Personalized Framework","publication_year":2022,"publication_date":"2022-03-01","ids":{"openalex":"https://openalex.org/W4220778421","doi":"https://doi.org/10.1142/s0218213022500245"},"language":"en","primary_location":{"id":"doi:10.1142/s0218213022500245","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213022500245","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","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/A5100344675","display_name":"Jinfeng Wang","orcid":"https://orcid.org/0000-0002-1246-4617"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfeng Wang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University, Guangzhou Key Laboratory of Intelligent Agriculture, Guangzhou, Guangdong, 510642, China"],"raw_orcid":"https://orcid.org/0000-0002-1246-4617","affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou Key Laboratory of Intelligent Agriculture, Guangzhou, Guangdong, 510642, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112633946","display_name":"Shuaihui Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuaihui Huang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, 510642, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, 510642, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059117888","display_name":"Junyang Liu","orcid":"https://orcid.org/0000-0002-7252-1900"},"institutions":[{"id":"https://openalex.org/I898250095","display_name":"Industrial and Commercial Bank of China","ror":"https://ror.org/02zcab046","country_code":"CN","type":"other","lineage":["https://openalex.org/I898250095"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyang Liu","raw_affiliation_strings":["Industrial and Commercial Bank of China, Zhuhai, Guangdong, 519000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Industrial and Commercial Bank of China, Zhuhai, Guangdong, 519000, China","institution_ids":["https://openalex.org/I898250095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050270789","display_name":"Dong Huang","orcid":"https://orcid.org/0000-0003-3923-8828"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Huang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, 510642, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, 510642, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100710326","display_name":"Wenzhong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzhong Wang","raw_affiliation_strings":["College of Economics and Management, South China Agricultural University, Guangzhou, Guangdong, 510642, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Economics and Management, South China Agricultural University, Guangzhou, Guangdong, 510642, China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7317,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70633425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"31","issue":"02","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9900000095367432,"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":0.9900000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8860130906105042},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5488215684890747},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5144779682159424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.506225049495697},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4537414312362671},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45218414068222046},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.44305747747421265},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.44124293327331543},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4263225197792053},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.37028923630714417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36643186211586},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3116850256919861},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.2146434783935547}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8860130906105042},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5488215684890747},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5144779682159424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506225049495697},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4537414312362671},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45218414068222046},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.44305747747421265},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.44124293327331543},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4263225197792053},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37028923630714417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36643186211586},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3116850256919861},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2146434783935547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"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:10.1142/s0218213022500245","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213022500245","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.49000000953674316,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4375867731","https://openalex.org/W2804364458","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"In":[0,82,124,198],"transportation,":[1],"drivers\u2019":[2],"state":[3],"directly":[4],"affects":[5],"traffic":[6],"safety.":[7,19],"Therefore,":[8],"an":[9,43,159],"accurate":[10,22],"driver\u2019s":[11,144,173],"fatigue":[12,28,38,115,129,138,145,174],"detection":[13,39,67,130,139,170,178,206],"is":[14,24,52,75,91,132],"crucial":[15],"for":[16,26,135],"ensuring":[17],"driving":[18],"Real-time":[20],"and":[21,47,57,163,217],"technology":[23],"needed":[25],"driver":[27,220],"detection.":[29],"To":[30],"address":[31],"this":[32,34],"problem,":[33],"article":[35],"proposes":[36],"a":[37,112,126,137],"method":[40,131,156,162,182],"based":[41,157],"on":[42,158],"improved":[44,160],"deep":[45],"learning":[46],"personalized":[48,127,201],"framework.":[49],"First,":[50],"clustering":[51,161],"applied":[53],"to":[54,62,78,94,141,225],"face":[55,80,104,128],"size,":[56],"cluster":[58],"numbers":[59],"are":[60,117],"used":[61],"determine":[63],"the":[64,70,79,83,86,95,98,103,107,121,143,154,169,195,200],"number":[65,87],"of":[66,72,88,114,172],"layers.":[68],"Then,":[69],"size":[71,105],"anchor":[73],"boxes":[74],"set":[76,92],"according":[77,93],"size.":[81],"proposed":[84,155,181,213],"framework,":[85],"convolutional":[89],"networks":[90],"principle":[96],"that":[97,153],"receptive":[99,165],"field":[100,166],"should":[101],"match":[102],"in":[106],"predicted":[108],"feature":[109],"map.":[110],"Finally,":[111],"variety":[113],"features":[116],"learned":[118],"by":[119,187],"minimizing":[120],"loss":[122],"function.":[123],"addition,":[125,199],"put":[133],"forward":[134],"building":[136],"framework":[140,202],"judge":[142],"status":[146],"more":[147],"reasonably.":[148],"The":[149,180,212],"experimental":[150],"results":[151],"show":[152],"local":[164],"can":[167,183,203,215,223],"improve":[168],"speed":[171],"while":[175,208],"maintaining":[176],"high":[177,205],"accuracy.":[179],"reach":[184],"125":[185],"fps":[186],"using":[188],"GPU":[189],"GeForce":[190],"GTX":[191],"TITAN,":[192],"which":[193,222],"satisfies":[194],"real-time":[196],"requirement.":[197],"achieve":[204],"accuracy":[207],"keeping":[209],"acceptable":[210],"speed.":[211],"model":[214],"accurately":[216],"timely":[218],"detect":[219],"fatigue,":[221],"help":[224],"avoid":[226],"accidents.":[227]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
