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dc.contributor.author전주형-
dc.contributor.author김현범-
dc.contributor.author한연재-
dc.contributor.author주영훈-
dc.contributor.author임선-
dc.contributor.author이승철-
dc.date.accessioned2020-11-30T02:50:52Z-
dc.date.available2020-11-30T02:50:52Z-
dc.date.created2020-11-30-
dc.date.issued2020-08-23-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/104408-
dc.publisherThe International Institute of Noise Control Engineering-
dc.relation.isPartOf49th International Congress and Exposition on Noise Control Engineering: Inter-Noise 2020-
dc.relation.isPartOf49th International Congress and Exposition on Noise Control Engineering: Inter-Noise 2020-
dc.titleArtificial Intelligence Approach for Detecting Pathological Voice-
dc.typeConference-
dc.type.rimsCONF-
dc.identifier.bibliographicCitation49th International Congress and Exposition on Noise Control Engineering: Inter-Noise 2020-
dc.citation.conferenceDate2020-08-23-
dc.citation.conferencePlaceKO-
dc.citation.title49th International Congress and Exposition on Noise Control Engineering: Inter-Noise 2020-
dc.contributor.affiliatedAuthor전주형-
dc.contributor.affiliatedAuthor이승철-
dc.description.journalClass1-
dc.description.journalClass1-

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이승철LEE, SEUNGCHUL
Dept of Mechanical Enginrg
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