{"id":"https://openalex.org/W2994424885","doi":"https://doi.org/10.1109/icawst.2019.8923343","title":"Effective feature extraction from driving data for detection of danger awareness","display_name":"Effective feature extraction from driving data for detection of danger awareness","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2994424885","doi":"https://doi.org/10.1109/icawst.2019.8923343","mag":"2994424885"},"language":"en","primary_location":{"id":"doi:10.1109/icawst.2019.8923343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2019.8923343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","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/A5104025685","display_name":"Kotaro Nakano","orcid":null},"institutions":[{"id":"https://openalex.org/I6090238","display_name":"Iwate Prefectural University","ror":"https://ror.org/054dx8336","country_code":"JP","type":"education","lineage":["https://openalex.org/I6090238"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kotaro Nakano","raw_affiliation_strings":["Graduate School of Software and Information Science, Iwate Prefectural University, JAPAN"],"affiliations":[{"raw_affiliation_string":"Graduate School of Software and Information Science, Iwate Prefectural University, JAPAN","institution_ids":["https://openalex.org/I6090238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101612450","display_name":"Basabi Chakraborty","orcid":"https://orcid.org/0000-0002-6211-9790"},"institutions":[{"id":"https://openalex.org/I6090238","display_name":"Iwate Prefectural University","ror":"https://ror.org/054dx8336","country_code":"JP","type":"education","lineage":["https://openalex.org/I6090238"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Basabi Chakraborty","raw_affiliation_strings":["Faculty of Software and Information Science, Iwate Prefectural University, JAPAN"],"affiliations":[{"raw_affiliation_string":"Faculty of Software and Information Science, Iwate Prefectural University, JAPAN","institution_ids":["https://openalex.org/I6090238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5104025685"],"corresponding_institution_ids":["https://openalex.org/I6090238"],"apc_list":null,"apc_paid":null,"fwci":0.1261,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.53010372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9736999869346619,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7006857991218567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6076654195785522},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.47029373049736023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4620710015296936},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38875579833984375}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7006857991218567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6076654195785522},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.47029373049736023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4620710015296936},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38875579833984375},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icawst.2019.8923343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2019.8923343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1538131130","https://openalex.org/W1993837778","https://openalex.org/W2011635588","https://openalex.org/W2060555212","https://openalex.org/W2099593264","https://openalex.org/W2104172517","https://openalex.org/W2133658999","https://openalex.org/W2733839197","https://openalex.org/W2774132735","https://openalex.org/W2776654602","https://openalex.org/W6632100814"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2601157893","https://openalex.org/W2131735617","https://openalex.org/W2373006798","https://openalex.org/W2056912418","https://openalex.org/W2123759770","https://openalex.org/W2033213769","https://openalex.org/W2811390910","https://openalex.org/W4312376745"],"abstract_inverted_index":{"In":[0,45],"recent":[1],"years,":[2],"the":[3,33,36,39,51,56,60,72,82,113,123,136,140,154,172,212],"importance":[4],"of":[5,41,55,59,71,81,116,125,148,159,162,175,178],"driver's":[6,99,137],"support":[7,22],"system":[8,76],"is":[9,151],"increasing":[10],"as":[11],"a":[12],"solution":[13],"for":[14,28,157,192,198,220],"dealing":[15],"with":[16,26,225],"car":[17],"related":[18],"accidents.":[19],"These":[20],"driving":[21,57,74,88,95,114,121,129,161,176,184,190,200,203,216],"systems":[23],"are":[24],"equipped":[25],"functions":[27],"avoiding":[29],"various":[30],"hazards":[31],"when":[32],"driver":[34,83,118,164],"drives":[35],"vehicle,":[37],"reducing":[38],"risk":[40],"causing":[42],"an":[43],"accident.":[44],"this":[46,149],"research,":[47],"we":[48],"focus":[49],"on":[50,64],"time":[52,167,224],"series":[53],"data":[54,90,174],"behaviour":[58,89,115,177],"driver,":[61],"and":[62,104,131,186,195,201],"based":[63,183,189,231],"these":[65,134],"data,":[66],"experiments":[67],"aiming":[68],"at":[69],"development":[70],"dangerous":[73],"detection":[75,158],"due":[77],"to":[78,152],"cognitive":[79],"distraction":[80,126,138],"have":[84,91,204],"been":[85,92,110,205],"conducted.":[86],"The":[87,146],"collected":[93,173],"from":[94,127,139,211],"simulator":[96],"which":[97],"contain":[98],"actions":[100],"mainly":[101],"steering,":[102],"accelerator":[103],"foot":[105],"brake":[106],"operations.":[107],"It":[108,207],"has":[109],"observed":[111],"that":[112,214],"each":[117],"changes":[119],"while":[120,128],"in":[122,165,222],"state":[124,142],"attentively":[130],"by":[132],"analyzing":[133],"changes,":[135],"normal":[141],"can":[143,208,217],"be":[144,209,218],"detected.":[145],"objective":[147],"paper":[150],"find":[153],"effective":[155],"features":[156],"distracted":[160,202,215],"specific":[163],"real":[166,223],"(specific":[168],"short":[169],"intervals).":[170],"From":[171],"multiple":[179],"subjects,":[180],"static":[181],"feature":[182,188,230],"model":[185,191],"dynamic":[187,229],"individual":[193,221],"drivers":[194,197],"all":[196],"attentive":[199],"developed.":[206],"shown":[210],"results":[213],"identified":[219],"stable":[226],"accuracy":[227],"using":[228],"models.":[232]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
