{"id":"https://openalex.org/W4406158129","doi":"https://doi.org/10.1109/tits.2024.3522308","title":"Calibration-Free Driver Drowsiness Classification With Prototype-Based Multi-Domain Mixup","display_name":"Calibration-Free Driver Drowsiness Classification With Prototype-Based Multi-Domain Mixup","publication_year":2025,"publication_date":"2025-01-08","ids":{"openalex":"https://openalex.org/W4406158129","doi":"https://doi.org/10.1109/tits.2024.3522308"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3522308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3522308","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","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":null,"display_name":"Dong-Young Kim","orcid":"https://orcid.org/0000-0002-6192-0770"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dong-Young Kim","raw_affiliation_strings":["Department of Artificial Intelligence, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024646050","display_name":"Dong\u2010Kyun Han","orcid":"https://orcid.org/0000-0002-8902-0678"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Kyun Han","raw_affiliation_strings":["Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068775765","display_name":"Ji-Hoon Jeong","orcid":"https://orcid.org/0000-0001-6940-2700"},"institutions":[{"id":"https://openalex.org/I163753206","display_name":"Chungbuk National University","ror":"https://ror.org/02wnxgj78","country_code":"KR","type":"education","lineage":["https://openalex.org/I163753206"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Ji-Hoon Jeong","raw_affiliation_strings":["School of Computer Science, Chungbuk National University, Cheongju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Chungbuk National University, Cheongju, South Korea","institution_ids":["https://openalex.org/I163753206"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011014617","display_name":"Seong\u2010Whan Lee","orcid":"https://orcid.org/0000-0002-6249-4996"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Whan Lee","raw_affiliation_strings":["Department of Artificial Intelligence, Korea University, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Korea University, Seoul, South Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":10.089,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.97591643,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"26","issue":"3","first_page":"2955","last_page":"2966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9987000226974487,"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"}},"topics":[{"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9932000041007996,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9679999947547913,"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/electroencephalography","display_name":"Electroencephalography","score":0.6373597383499146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.510424792766571},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.48906928300857544},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.48290276527404785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4815812110900879},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4655708968639374},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4531354308128357},{"id":"https://openalex.org/keywords/driving-simulator","display_name":"Driving simulator","score":0.4300996661186218},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41114896535873413},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3350033760070801},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2541995048522949},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14650088548660278},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10717445611953735}],"concepts":[{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6373597383499146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.510424792766571},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.48906928300857544},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.48290276527404785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4815812110900879},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4655708968639374},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4531354308128357},{"id":"https://openalex.org/C2780689630","wikidata":"https://www.wikidata.org/wiki/Q2081815","display_name":"Driving simulator","level":2,"score":0.4300996661186218},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41114896535873413},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3350033760070801},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2541995048522949},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14650088548660278},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10717445611953735},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","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/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3522308","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3522308","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2002881556","https://openalex.org/W2128404967","https://openalex.org/W2170498360","https://openalex.org/W2559463885","https://openalex.org/W2589408790","https://openalex.org/W2741907166","https://openalex.org/W2793667632","https://openalex.org/W2795547633","https://openalex.org/W2886857653","https://openalex.org/W2890363742","https://openalex.org/W2908578648","https://openalex.org/W2949813473","https://openalex.org/W2980306787","https://openalex.org/W2986984881","https://openalex.org/W3007820043","https://openalex.org/W3012521722","https://openalex.org/W3035743198","https://openalex.org/W3041698047","https://openalex.org/W3081155232","https://openalex.org/W3083752628","https://openalex.org/W3109831211","https://openalex.org/W3114735065","https://openalex.org/W3124412656","https://openalex.org/W3133542152","https://openalex.org/W3134961575","https://openalex.org/W3153663385","https://openalex.org/W3154974560","https://openalex.org/W3162595154","https://openalex.org/W3163437748","https://openalex.org/W3179233662","https://openalex.org/W3212715905","https://openalex.org/W3214662938","https://openalex.org/W4205519040","https://openalex.org/W4206066711","https://openalex.org/W4289639938","https://openalex.org/W4301040613","https://openalex.org/W4306729455","https://openalex.org/W4309345155","https://openalex.org/W4312309619","https://openalex.org/W4312943213","https://openalex.org/W4381733655","https://openalex.org/W4394799282","https://openalex.org/W4400524974"],"related_works":["https://openalex.org/W2591697403","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2359348847","https://openalex.org/W3011538607","https://openalex.org/W2171218219","https://openalex.org/W4294432981","https://openalex.org/W4321441197","https://openalex.org/W1972271943","https://openalex.org/W2922348724"],"abstract_inverted_index":{"Drowsy":[0],"driving":[1],"is":[2,32,49],"one":[3],"of":[4,15,44,98,109,126,133,199,213,227],"the":[5,13,41,45,53,83,96,127,131,134,156,175,185,207,222],"greatest":[6],"threats":[7],"to":[8,34,91,112,151],"road":[9],"safety,":[10],"which":[11,87],"increases":[12],"importance":[14],"intelligent":[16],"systems":[17,26],"that":[18,39],"can":[19,88],"monitor":[20],"driver":[21,78],"drowsiness.":[22],"Electroencephalogram":[23],"(EEG)\u2013based":[24],"monitoring":[25],"have":[27],"gained":[28],"attention":[29],"because":[30,55],"EEG":[31,56,167],"known":[33],"directly":[35],"measure":[36],"brain":[37],"activities":[38],"reflect":[40],"mental":[42],"state":[43],"driver.":[46],"However,":[47],"calibration":[48],"necessary":[50],"before":[51],"using":[52,165,171],"system":[54],"signals":[57],"vary":[58],"between":[59,107],"and":[60,179,201,203,215],"within":[61],"subjects.":[62,93],"Therefore,":[63],"generalized":[64,90],"EEG-based":[65,77],"drowsiness":[66,79,173],"estimation":[67,154],"has":[68],"become":[69],"challenging.":[70],"In":[71,182],"this":[72],"paper,":[73],"we":[74,141],"propose":[75],"an":[76,143,194,204],"classification":[80],"framework":[81,187],"without":[82,230],"need":[84],"for":[85,137,148,224],"calibration,":[86],"be":[89],"unseen":[92,99],"We":[94],"augment":[95],"features":[97],"domains":[100,111],"(i.e.,":[101],"subjects)":[102],"with":[103],"a":[104],"Dirichlet":[105,128],"mixup":[106],"prototypes":[108],"source":[110],"complement":[113],"other":[114],"domain":[115],"knowledge.":[116],"The":[117,160,218],"parameter":[118],"<inline-formula":[119],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[120,196],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[121],"<tex-math":[122],"notation=\"LaTeX\">$\\boldsymbol{\\alpha}$</tex-math>":[123],"</inline-formula>":[124],"vector":[125],"distribution":[129],"adjusts":[130],"intensity":[132],"mixup,":[135],"allowing":[136],"diverse":[138],"enhancement.":[139],"Furthermore,":[140],"utilize":[142],"auxiliary":[144],"batch":[145],"normalization":[146],"module":[147],"augmented":[149],"samples":[150],"avoid":[152],"inaccurate":[153],"by":[155],"difference":[157],"in":[158,191],"distribution.":[159],"experiments":[161],"were":[162],"carried":[163],"out":[164],"two":[166],"datasets,":[168,193],"each":[169],"measured":[170],"different":[172],"indicators,":[174],"Karolinska":[176],"sleepiness":[177],"scale,":[178],"reaction":[180],"time.":[181],"leave-one-subject-out":[183],"cross-validation,":[184],"proposed":[186],"achieved":[188],"outstanding":[189],"performance":[190],"both":[192],"<italic":[195],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">F</i>":[197],"1-score":[198],"62.69%":[200],"70.33%":[202],"area":[205],"under":[206],"receiver":[208],"operating":[209],"characteristic":[210],"curve":[211],"(AUROC)":[212],"71.73%":[214],"73.80%,":[216],"respectively.":[217],"experimental":[219],"results":[220],"demonstrate":[221],"potential":[223],"practical":[225],"applications":[226],"brain-computer":[228],"interfaces":[229],"calibration.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
