{"id":"https://openalex.org/W2293060818","doi":"https://doi.org/10.1109/bigcomp.2016.7425813","title":"Real-time categorization of driver's gaze zone using the deep learning techniques","display_name":"Real-time categorization of driver's gaze zone using the deep learning techniques","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2293060818","doi":"https://doi.org/10.1109/bigcomp.2016.7425813","mag":"2293060818"},"language":"en","primary_location":{"id":"doi:10.1109/bigcomp.2016.7425813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2016.7425813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Big Data and Smart Computing (BigComp)","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/A5045512819","display_name":"In-Ho Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"In-Ho Choi","raw_affiliation_strings":["Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044088026","display_name":"Sung Kyung Hong","orcid":"https://orcid.org/0000-0003-1143-2194"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sung Kyung Hong","raw_affiliation_strings":["Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064727471","display_name":"Yong-Guk Kim","orcid":"https://orcid.org/0000-0003-4645-1395"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong-Guk Kim","raw_affiliation_strings":["Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng., Sejong University, Kwangjin-Gu, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045512819"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":null,"apc_paid":null,"fwci":7.287,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":{"value":0.97410215,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"143","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.978600025177002,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/gaze","display_name":"Gaze","score":0.818840742111206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8010990619659424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7498131990432739},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7245186567306519},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6737631559371948},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.6736050844192505},{"id":"https://openalex.org/keywords/distraction","display_name":"Distraction","score":0.5131850838661194},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5124083161354065},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.48418882489204407},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.470800518989563},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45165032148361206},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42115259170532227},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32884112000465393}],"concepts":[{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.818840742111206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8010990619659424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7498131990432739},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7245186567306519},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6737631559371948},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.6736050844192505},{"id":"https://openalex.org/C2776378700","wikidata":"https://www.wikidata.org/wiki/Q3030775","display_name":"Distraction","level":2,"score":0.5131850838661194},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5124083161354065},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.48418882489204407},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.470800518989563},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45165032148361206},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42115259170532227},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32884112000465393},{"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},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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/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:10.1109/bigcomp.2016.7425813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigcomp.2016.7425813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Big Data and Smart Computing (BigComp)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1606347560","https://openalex.org/W1963841851","https://openalex.org/W1964846093","https://openalex.org/W2088696604","https://openalex.org/W2116208238","https://openalex.org/W2143925122","https://openalex.org/W2155893237","https://openalex.org/W2163605009","https://openalex.org/W6636358008","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1984342691","https://openalex.org/W2470048815","https://openalex.org/W2324884046","https://openalex.org/W641612223","https://openalex.org/W2906771794","https://openalex.org/W2028203774","https://openalex.org/W2027724706","https://openalex.org/W2161294397","https://openalex.org/W2012644758","https://openalex.org/W2047559669"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,24,48,59,72,82,88,92,111,130,136,147,150],"study":[4],"in":[5,76,157,174],"which":[6,84],"driver's":[7,126],"gaze":[8,21,102,127,168,183],"zone":[9,128,169,184],"is":[10,56,81,113,122],"categorized":[11],"using":[12,87,135],"new":[13],"deep":[14],"learning":[15],"techniques.":[16,192],"Since":[17],"the":[18,44,66,77,98,158,164,181],"sequence":[19],"of":[20,23,105,167],"zones":[22,103],"driver":[25,112],"reflects":[26],"precisely":[27],"what":[28],"and":[29,139],"how":[30],"he":[31],"behaves,":[32],"it":[33],"allows":[34],"us":[35],"infer":[36],"his":[37],"drowsiness,":[38],"focusing":[39],"or":[40],"distraction":[41],"by":[42,95],"analyzing":[43],"images":[45],"coming":[46],"from":[47,129],"camera.":[49],"A":[50,118],"Haar":[51],"feature":[52],"based":[53,62,187],"face":[54,67,132],"detector":[55],"combined":[57],"with":[58],"correlation":[60],"filter":[61],"MOSS":[63],"tracker":[64],"for":[65],"detection":[68],"task":[69],"to":[70,124,146,155,172],"handle":[71],"tough":[73],"visual":[74],"environment":[75],"car.":[78],"Driving":[79],"database":[80],"big-data":[83],"was":[85],"constructed":[86],"recording":[89],"setup":[90],"within":[91,149],"compact":[93],"sedan":[94],"driving":[96],"around":[97],"urban":[99],"area.":[100],"The":[101],"consist":[104],"9":[106],"categories":[107],"depending":[108],"on":[109,153,188],"where":[110],"looking":[114],"at":[115],"during":[116],"driving.":[117],"convolutional":[119],"neural":[120],"network":[121,142],"trained":[123],"categorize":[125],"given":[131],"detected":[133],"image":[134],"multi-GPU":[137],"platform,":[138],"then":[140],"its":[141],"parameters":[143],"are":[144],"transferred":[145],"GPU":[148],"PC":[151],"running":[152],"Windows":[154],"operate":[156],"real-time":[159],"basis.":[160],"Result":[161],"suggests":[162],"that":[163,177],"correct":[165],"rate":[166],"categorization":[170,185],"reaches":[171],"95%":[173],"average,":[175],"indicating":[176],"our":[178],"system":[179],"outperforms":[180],"state-of-art":[182],"methods":[186],"conventional":[189],"computer":[190],"vision":[191]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}