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Achieving an optimal group structure in a neural architecture search

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dc.contributor.authorSeo, W.-
dc.contributor.authorPark, J.-
dc.contributor.authorLim, W.-
dc.contributor.authorKim, Dae-Won-
dc.contributor.authorLee, Jaesung-
dc.date.accessioned2022-10-20T06:40:32Z-
dc.date.available2022-10-20T06:40:32Z-
dc.date.issued2022-09-
dc.identifier.issn0013-5194-
dc.identifier.issn1350-911X-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/58854-
dc.description.abstractThe method proposed in this letter searches for an effective group structure of group convolutions in a convolutional neural network that can improve the classification accuracy. The model's group structure is obtained using an effective differential neural architecture search. Our code can be accessed at https://github.com/minercode625/grunas.git. © 2022 The Authors. Electronics Letters published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.-
dc.format.extent2-
dc.language영어-
dc.language.isoENG-
dc.publisherJohn Wiley and Sons Inc-
dc.titleAchieving an optimal group structure in a neural architecture search-
dc.typeArticle-
dc.identifier.doi10.1049/ell2.12585-
dc.identifier.bibliographicCitationElectronics Letters, v.58, no.19, pp 732 - 733-
dc.description.isOpenAccessY-
dc.identifier.wosid000832593900001-
dc.identifier.scopusid2-s2.0-85135176776-
dc.citation.endPage733-
dc.citation.number19-
dc.citation.startPage732-
dc.citation.titleElectronics Letters-
dc.citation.volume58-
dc.type.docTypeArticle-
dc.publisher.location영국-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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