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dc.contributor.author김은현-
dc.contributor.author김동덕-
dc.contributor.author서영주-
dc.date.accessioned2021-06-01T10:55:46Z-
dc.date.available2021-06-01T10:55:46Z-
dc.date.created2021-03-21-
dc.date.issued2020-02-06-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/106317-
dc.languageKorean-
dc.publisher한국통신학회-
dc.relation.isPartOf2020년도 한국통신학회 동계종합학술발표회-
dc.relation.isPartOf2020년도 한국통신학회 동계종합학술발표회 논문집-
dc.title합성곱신경망 기반 WiFi 채널 상태 정보를 이용한 제스처 인식-
dc.title.alternativeConvolutional Neural Network Based Gesture Recognition Using WiFi Channel State Information-
dc.typeConference-
dc.type.rimsCONF-
dc.identifier.bibliographicCitation2020년도 한국통신학회 동계종합학술발표회-
dc.citation.conferenceDate2020-02-05-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace강원도 평창군 용평리조트-
dc.citation.title2020년도 한국통신학회 동계종합학술발표회-
dc.contributor.affiliatedAuthor김은현-
dc.contributor.affiliatedAuthor김동덕-
dc.contributor.affiliatedAuthor서영주-
dc.description.journalClass2-
dc.description.journalClass2-

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서영주SUH, YOUNG JOO
Grad. School of AI
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