{"id":"https://openalex.org/W3116280467","doi":"https://doi.org/10.1109/itsc45102.2020.9294659","title":"Fast Semi-Supervised Anomaly Detection of Drivers\u2019 Behavior using Online Sequential Extreme Learning Machine","display_name":"Fast Semi-Supervised Anomaly Detection of Drivers\u2019 Behavior using Online Sequential Extreme Learning Machine","publication_year":2020,"publication_date":"2020-09-20","ids":{"openalex":"https://openalex.org/W3116280467","doi":"https://doi.org/10.1109/itsc45102.2020.9294659","mag":"3116280467"},"language":"en","primary_location":{"id":"doi:10.1109/itsc45102.2020.9294659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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/A5015933802","display_name":"Hiroki Oikawa","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroki Oikawa","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002218612","display_name":"Tomoya Nishida","orcid":"https://orcid.org/0000-0002-7941-9984"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoya Nishida","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102711746","display_name":"Ryuichi Sakamoto","orcid":"https://orcid.org/0000-0002-2999-100X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryuichi Sakamoto","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041549339","display_name":"Hiroki Matsutani","orcid":"https://orcid.org/0000-0001-9578-3842"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Matsutani","raw_affiliation_strings":["Keio University, Yokohama, Japan"],"affiliations":[{"raw_affiliation_string":"Keio University, Yokohama, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103017591","display_name":"Masaaki Kondo","orcid":"https://orcid.org/0000-0002-6025-8738"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Kondo","raw_affiliation_strings":["Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5015933802"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70125958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.984000027179718,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/anomaly-detection","display_name":"Anomaly detection","score":0.8977946639060974},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7617337703704834},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6902998089790344},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6356978416442871},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6310391426086426},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.6245818138122559},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5732071995735168},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5063561201095581},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.49161630868911743},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4498459994792938},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.41571423411369324},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3738037347793579},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.358310729265213}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8977946639060974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7617337703704834},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6902998089790344},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6356978416442871},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6310391426086426},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6245818138122559},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5732071995735168},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5063561201095581},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.49161630868911743},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4498459994792938},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.41571423411369324},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3738037347793579},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.358310729265213},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc45102.2020.9294659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc45102.2020.9294659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)","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":22,"referenced_works":["https://openalex.org/W31566076","https://openalex.org/W1489490800","https://openalex.org/W1521186642","https://openalex.org/W2086699924","https://openalex.org/W2094783644","https://openalex.org/W2100495367","https://openalex.org/W2111072639","https://openalex.org/W2116261113","https://openalex.org/W2133160602","https://openalex.org/W2139902660","https://openalex.org/W2158054309","https://openalex.org/W2463415820","https://openalex.org/W2590652386","https://openalex.org/W2753352458","https://openalex.org/W2884781549","https://openalex.org/W2902455138","https://openalex.org/W2908324624","https://openalex.org/W2963513865","https://openalex.org/W6601248315","https://openalex.org/W6677408996","https://openalex.org/W6756753118","https://openalex.org/W6757581798"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"With":[0],"the":[1,25,45,125,141,161,185,190,198,216],"wide":[2],"spread":[3],"of":[4,24,28,36,48,127,137,143],"artificial":[5],"intelligence":[6],"(AI)":[7],"technologies,":[8],"many":[9,17],"applications":[10,27],"using":[11,134],"AI":[12,64],"are":[13],"increasingly":[14],"deployed":[15],"in":[16,204],"fields.":[18],"Specially":[19],"anomaly":[20,34,60,102,130,172,193,205],"detection":[21,62,207],"is":[22,52,73,96,167],"one":[23],"key":[26],"AI.":[29],"Among":[30],"several":[31],"targets,":[32],"detecting":[33],"behavior":[35,132,164],"drivers":[37],"or":[38,200,218],"vehicles":[39,138],"has":[40,81,105,196],"been":[41,108],"attracting":[42,76],"due":[43],"to":[44,54,98],"growing":[46],"demand":[47],"safety":[49],"driving.":[50],"It":[51],"crucial":[53],"study":[55,124],"and":[56,85,139,152],"evaluate":[57],"techniques":[58],"for":[59,101,110,170],"driving":[61,117,131,163,194,206],"with":[63,91,145,180,208,215],"technologies.":[65],"The":[66],"Online":[67],"Sequential":[68],"Extreme":[69],"Learning":[70],"Machine":[71],"(OS-ELM)":[72],"a":[74,146,177,181],"recently":[75],"neural":[77],"network":[78],"model":[79],"that":[80,189],"high":[82],"memory":[83],"efficiency":[84],"can":[86],"perform":[87],"highspeed":[88],"sequential":[89,211],"learning":[90,212],"streaming":[92],"data.":[93,119],"Though":[94],"OSELM":[95],"known":[97],"be":[99],"effective":[100],"detection,":[103],"it":[104,144],"not":[106,168],"yet":[107],"verified":[109],"non-stationary":[111],"time":[112],"series":[113],"data":[114,136,166],"such":[115],"as":[116],"sensor":[118,135],"In":[120],"this":[121],"paper,":[122],"we":[123,174,187],"effectiveness":[126],"OS-ELM":[128,191],"based":[129,151,158,192,220],"detector":[133,195],"compared":[140,214],"performance":[142],"Hidden":[147],"Markov":[148],"Model":[149],"(HMM)":[150],"traditional":[153],"Long":[154],"Short-Term":[155],"Memory":[156],"(LSTM)":[157],"methods.":[159],"Since":[160],"existing":[162],"benchmark":[165],"enough":[169],"evaluating":[171],"driving,":[173],"also":[175],"create":[176],"new":[178],"dataset":[179],"powered":[182],"wheelchair.":[183],"Throughout":[184],"evaluation,":[186],"show":[188],"almost":[197],"same":[199],"even":[201],"better":[202],"accuracy":[203],"much":[209],"faster":[210],"speed":[213],"HMM":[217],"LSTM":[219],"detector.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}