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dc.contributor.authorSEUNG, HYUN JEONG-
dc.contributor.author박영덕-
dc.contributor.author이상윤-
dc.contributor.author서영주-
dc.date.accessioned2022-03-02T05:26:43Z-
dc.date.available2022-03-02T05:26:43Z-
dc.date.created2022-02-25-
dc.date.issued2019-01-24-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/110006-
dc.languageKorean-
dc.publisher-
dc.relation.isPartOf2019년도 한국통신학회 동계종합학술발표회-
dc.relation.isPartOf2019년도 한국통신학회 동계종합학술발표회 논문집-
dc.titleWiFi 채널 상태 정보를 이용한 딥러닝 기반 호흡 및 심박 패턴 인식 방법-
dc.title.alternativeDeep Learning-based Breathing Pattern Recognition Method Using WiFi Channel State Information-
dc.typeConference-
dc.type.rimsCONF-
dc.identifier.bibliographicCitation2019년도 한국통신학회 동계종합학술발표회-
dc.citation.conferenceDate2019-01-23-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace강원도 평창군 용평리조트-
dc.citation.title2019년도 한국통신학회 동계종합학술발표회-
dc.contributor.affiliatedAuthorSEUNG, HYUN JEONG-
dc.contributor.affiliatedAuthor박영덕-
dc.contributor.affiliatedAuthor서영주-
dc.description.journalClass2-
dc.description.journalClass2-

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서영주SUH, YOUNG JOO
Grad. School of AI
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