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Avoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approach

dc.contributor.authorCarballal, A
dc.contributor.authorFernandez Lozano, Carlos
dc.contributor.authorRodriguez-Fernandez, N
dc.contributor.authorCastro, L
dc.contributor.authorSantos, A
dc.date.accessioned2022-02-02T08:16:55Z
dc.date.available2022-02-02T08:16:55Z
dc.date.issued2019
dc.identifier.issn1076-2787
dc.identifier.urihttp://hdl.handle.net/20.500.11940/16073
dc.language.isoenges
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleAvoiding the Inherent Limitations in Datasets Used for Measuring Aesthetics When Using a Machine Learning Approachen
dc.typeArtigoes
dc.identifier.doi10.1155/2019/4659809
dc.identifier.sophos34786
dc.journal.titleCOMPLEXITY.es
dc.organizationServizo Galego de Saúde::Estrutura de Xestión Integrada (EOXI)::Instituto de Investigación Biomédica da Coruña (INIBIC)es
dc.page.initial1es
dc.relation.publisherversionhttps://downloads.hindawi.com/journals/complexity/2019/4659809.pdfes
dc.rights.accessRightsopenAccesses
dc.subject.keywordINIBICes
dc.typefidesArtículo Originales
dc.typesophosArtículo Originales
dc.volume.number-es


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