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Long Short Term Memory 기반의 운전자 행동 모니터링 시스템

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dc.contributor.author양진호-
dc.contributor.author이현수-
dc.contributor.author최우영-
dc.contributor.author정정주-
dc.date.accessioned2021-08-10T01:30:13Z-
dc.date.available2021-08-10T01:30:13Z-
dc.date.created2021-08-10-
dc.date.issued2018-06-07-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/87642-
dc.description.abstractThe driver behavior monitoring system is a system for observing unexpected maneuvers of a driver and alerting dangerous situation to prevent traffic accidents. In this paper, we propose the ‘Long Short Term Memory (LSTM)’ based driver behavior monitoring system. The LSTM is suitable for monitoring driver`s behavior because it is easy to process long term sequential data through selective memory algorithm using the partially storing method. The verification about the prediction simulation was conducted by comparing the actual driving data and the prediction results using the LSTM which implemented by computer language.-
dc.language한국어-
dc.language.isoko-
dc.publisher한국자동차공학회-
dc.titleLong Short Term Memory 기반의 운전자 행동 모니터링 시스템-
dc.title.alternativeLong short Term Memory Based Driver Behavior Monitoring System-
dc.typeConference-
dc.contributor.affiliatedAuthor정정주-
dc.identifier.bibliographicCitation한국자동차공학회 2018 춘계학술대회 , pp.862 - 867-
dc.relation.isPartOf한국자동차공학회 2018 춘계학술대회-
dc.relation.isPartOf2018 한국자동차공학회 춘계학술대회-
dc.citation.title한국자동차공학회 2018 춘계학술대회-
dc.citation.startPage862-
dc.citation.endPage867-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace부산 벡스코-
dc.citation.conferenceDate2018-06-07-
dc.type.rimsCONF-
dc.description.journalClass2-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07546710-
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서울 공과대학 > 서울 전기공학전공 > 2. Conference Papers

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