{"id":"https://openalex.org/W3174359619","doi":"https://doi.org/10.1109/icit46573.2021.9453521","title":"A System For Drivers\u2019 Cognitive Load Estimation Based On Deep Convolutional Neural Networks and Facial Feature Analysis","display_name":"A System For Drivers\u2019 Cognitive Load Estimation Based On Deep Convolutional Neural Networks and Facial Feature Analysis","publication_year":2021,"publication_date":"2021-03-10","ids":{"openalex":"https://openalex.org/W3174359619","doi":"https://doi.org/10.1109/icit46573.2021.9453521","mag":"3174359619"},"language":"en","primary_location":{"id":"doi:10.1109/icit46573.2021.9453521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit46573.2021.9453521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 22nd IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-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/A5032067468","display_name":"Shyngyskhan Abilkassov","orcid":null},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":true,"raw_author_name":"Shyngyskhan Abilkassov","raw_affiliation_strings":["School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069275517","display_name":"Merey Kairgaliyev","orcid":null},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Merey Kairgaliyev","raw_affiliation_strings":["School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005724730","display_name":"Bauyrzhan Zhakanov","orcid":null},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Bauyrzhan Zhakanov","raw_affiliation_strings":["School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041371940","display_name":"Berdakh Abibullaev","orcid":"https://orcid.org/0000-0002-8623-5526"},"institutions":[{"id":"https://openalex.org/I60559429","display_name":"Nazarbayev University","ror":"https://ror.org/052bx8q98","country_code":"KZ","type":"education","lineage":["https://openalex.org/I60559429"]}],"countries":["KZ"],"is_corresponding":false,"raw_author_name":"Berdakh Abibullaev","raw_affiliation_strings":["School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan","institution_ids":["https://openalex.org/I60559429"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032067468"],"corresponding_institution_ids":["https://openalex.org/I60559429"],"apc_list":null,"apc_paid":null,"fwci":0.1753,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53499591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"994","last_page":"1000"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9998999834060669,"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/T11373","display_name":"Sleep and Work-Related Fatigue","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/T10370","display_name":"Traffic and Road Safety","score":0.9675999879837036,"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"}},{"id":"https://openalex.org/T12006","display_name":"Ergonomics and Musculoskeletal Disorders","score":0.9642999768257141,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7844690084457397},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7351979613304138},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7215284109115601},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6732783317565918},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5884910225868225},{"id":"https://openalex.org/keywords/distraction","display_name":"Distraction","score":0.528073787689209},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.47870495915412903},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4681186079978943},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4579443335533142},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4538224935531616},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42617231607437134},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.4120270907878876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4038710594177246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33296966552734375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7844690084457397},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7351979613304138},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7215284109115601},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6732783317565918},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5884910225868225},{"id":"https://openalex.org/C2776378700","wikidata":"https://www.wikidata.org/wiki/Q3030775","display_name":"Distraction","level":2,"score":0.528073787689209},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.47870495915412903},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4681186079978943},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4579443335533142},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4538224935531616},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42617231607437134},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.4120270907878876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4038710594177246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33296966552734375},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit46573.2021.9453521","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icit46573.2021.9453521","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 22nd IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W116278252","https://openalex.org/W1532499804","https://openalex.org/W1594790245","https://openalex.org/W1965576908","https://openalex.org/W2038956261","https://openalex.org/W2071878275","https://openalex.org/W2077946593","https://openalex.org/W2089583421","https://openalex.org/W2115252128","https://openalex.org/W2118166874","https://openalex.org/W2146182319","https://openalex.org/W2194775991","https://openalex.org/W2282606863","https://openalex.org/W2324736398","https://openalex.org/W2509901229","https://openalex.org/W2523947784","https://openalex.org/W2572052422","https://openalex.org/W2595203562","https://openalex.org/W2610697518","https://openalex.org/W2885876042","https://openalex.org/W2943512776","https://openalex.org/W2963573361","https://openalex.org/W4245563784","https://openalex.org/W6631754287","https://openalex.org/W6677618333","https://openalex.org/W6731801541","https://openalex.org/W6766290778"],"related_works":["https://openalex.org/W1984342691","https://openalex.org/W641612223","https://openalex.org/W2906771794","https://openalex.org/W2783719297","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,127],"driver's":[1,46,77,105,218,240],"cognitive":[2,78],"load":[3],"estimation":[4,74,121],"on":[5,49,60,72,100,226,245],"the":[6,18,53,61,73,76,84,104,133,140,144,151,155,180,183,197,205,208,217,232,239],"road":[7,22],"is":[8,130],"a":[9,45,66,230],"critical":[10,58],"factor":[11],"for":[12,117,159,191],"safety":[13,242],"measurement":[14],"that":[15],"can":[16,40],"reduce":[17],"overall":[19],"number":[20,54],"of":[21,55,75,86,139,199],"accidents.":[23],"Factors":[24],"such":[25],"as":[26],"distraction":[27],"from":[28,103,174,179],"driving,":[29],"being":[30],"\"lost":[31],"in":[32],"thought,\"":[33],"conversation,":[34],"cell":[35],"phone":[36],"use,":[37],"and":[38,57,82,107,146,195,251],"drowsiness,":[39],"be":[41,189],"used":[42,190,213],"to":[43,188,214,237],"compute":[44],"attention":[47],"level":[48,120,220,243],"driving.":[50],"To":[51],"minimize":[52],"fatal":[56],"circumstances":[59],"road,":[62],"this":[63],"work":[64],"investigates":[65],"decision":[67,233],"tree-based":[68],"deep-learning":[69],"algorithm":[70],"focusing":[71],"load.":[79],"We":[80],"construct":[81],"evaluate":[83],"performance":[85],"multimodal":[87],"deep":[88,192,246],"learning":[89,193,247],"approaches,":[90],"which":[91],"combine":[92],"two":[93,114],"separately":[94],"trained":[95],"ResNet50":[96],"convolutional":[97],"neural":[98],"networks":[99],"data":[101],"acquired":[102],"side":[106,175,248],"front":[108],"face":[109,141],"images.":[110],"Further,":[111],"we":[112],"compare":[113],"different":[115,123],"approaches":[116],"driver":[118,168],"drowsiness":[119,160,219],"using":[122,137,162,222],"computer":[124,223],"vision":[125,224],"algorithms.":[126],"first":[128],"approach":[129,158],"implemented":[131],"via":[132],"blinking":[134,145,252],"ratio":[135,253],"method":[136],"68-landmarks":[138],"by":[142,221],"calculating":[143],"yawning":[147],"ratio.":[148],"In":[149],"contrast,":[150],"second":[152],"one":[153],"uses":[154],"contour":[156],"area":[157],"identification":[161],"morphological":[163],"operations.":[164],"As":[165,229],"differences":[166],"between":[167],"behavioral":[169],"classes":[170],"are":[171],"more":[172],"distinct":[173],"camera":[176],"images":[177],"than":[178],"frontal":[181,209],"image,":[182],"former":[184],"has":[185,201],"been":[186,202],"chosen":[187],"classification,":[194],"eventually,":[196],"accuracy":[198],"92%":[200],"achieved.":[203],"On":[204],"other":[206],"hand,":[207],"image":[210],"was":[211,235],"successfully":[212],"robustly":[215],"detect":[216],"techniques":[225],"facial":[227],"landmarks.":[228],"result,":[231],"tree":[234],"constructed":[236],"estimate":[238],"driving":[241],"based":[244],"posture":[249],"classification":[250],"methods.":[254]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
