VATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks

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dc.contributor.authorPark, Cheonbokko
dc.contributor.authorYang, Soyoungko
dc.contributor.authorNa, Inyoupko
dc.contributor.authorChung, Sunghyoko
dc.contributor.authorShin, Sungbokko
dc.contributor.authorKwon, Bumchulko
dc.contributor.authorPark, Deokgunko
dc.contributor.authorChoo, Jaegulko
dc.date.accessioned2022-01-14T06:56:22Z-
dc.date.available2022-01-14T06:56:22Z-
dc.date.created2021-12-03-
dc.date.created2021-12-03-
dc.date.issued2021-06-14-
dc.identifier.citationEurovis 2021 : Eurographics/IEEE Symposium on Visualization-
dc.identifier.urihttp://hdl.handle.net/10203/291832-
dc.languageEnglish-
dc.publisherEurovis-
dc.titleVATUN: Visual Analytics for Testing and Understanding Convolutional Neural Networks-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameEurovis 2021 : Eurographics/IEEE Symposium on Visualization-
dc.identifier.conferencecountrySZ-
dc.identifier.conferencelocationZurich-
dc.contributor.localauthorChoo, Jaegul-
dc.contributor.nonIdAuthorPark, Cheonbok-
dc.contributor.nonIdAuthorYang, Soyoung-
dc.contributor.nonIdAuthorNa, Inyoup-
dc.contributor.nonIdAuthorChung, Sunghyo-
dc.contributor.nonIdAuthorShin, Sungbok-
dc.contributor.nonIdAuthorKwon, Bumchul-
dc.contributor.nonIdAuthorPark, Deokgun-
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AI-Conference Papers(학술대회논문)
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