Extrapolating continuous color emotions through deep learning

dc.authorscopusid57221150141
dc.authorscopusid55652378300
dc.authorscopusid55927872000
dc.authorscopusid57192306774
dc.authorscopusid18537242000
dc.authorscopusid7801349425
dc.authorscopusid56426551700
dc.contributor.authorManav, Banu
dc.contributor.authorSchaposnik,L.P.
dc.contributor.authorKonstantinou,N.
dc.contributor.authorVolkan,E.
dc.contributor.authorPapadatou-Pastou,M.
dc.contributor.authorManav,B.
dc.contributor.authorMohr,C.
dc.date.accessioned2024-10-15T19:42:03Z
dc.date.available2024-10-15T19:42:03Z
dc.date.issued2020
dc.departmentKadir Has Universityen_US
dc.department-tempRam V., Milton High School, Milton, 30004, GA, United States; Schaposnik L.P., Department of Mathematics, Statistics and Computer Science, University of Illinois, Chicago, 60607, IL, United States; Konstantinou N., Department of Rehabilitation Sciences, Faculty of Health Sciences, Cyprus University of Technology, Limassol, 3036, Cyprus; Volkan E., Department of Psychology, Cyprus International University, Nicosia, 99258, Cyprus; Papadatou-Pastou M., National and Kapodistrian University of Athens, Athens, 157 72, Greece; Manav B., Kadir Has University, Faculty of Art and Design, Department of Interior Architecture and Environmental Design, Kadir Has Caddesi, Cibali-İstanbul, 34083, Turkey; Jonauskaite D., Institute of Psychology, University of Lausanne, Lausanne, 1015, Switzerland; Mohr C., Institute of Psychology, University of Lausanne, Lausanne, 1015, Switzerlanden_US
dc.description.abstractBy means of an experimental dataset, we use deep learning to implement an RGB (red, green, and blue) extrapolation of emotions associated to color, and do a mathematical study of the results obtained through this neural network. In particular, we see that males (type-m individuals) typically associate a given emotion with darker colors, while females (type-f individuals) associate it with brighter colors. A similar trend was observed with older people and associations to lighter colors. Moreover, through our classification matrix, we identify which colors have weak associations to emotions and which colors are typically confused with other colors. © 2020 authors. Published by the American Physical Society.en_US
dc.description.sponsorshipDirectorate for Mathematical and Physical Sciences, MPS, (1749013)en_US
dc.identifier.citation7
dc.identifier.doi10.1103/PhysRevResearch.2.033350
dc.identifier.issn2643-1564
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85113520218
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1103/PhysRevResearch.2.033350
dc.identifier.urihttps://hdl.handle.net/20.500.12469/6512
dc.identifier.volume2en_US
dc.language.isoenen_US
dc.publisherAmerican Physical Societyen_US
dc.relation.ispartofPhysical Review Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject[No Keyword Available]en_US
dc.titleExtrapolating continuous color emotions through deep learningen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublicationd11f6424-2d69-45f8-9d15-5faa04038be1
relation.isAuthorOfPublication.latestForDiscoveryd11f6424-2d69-45f8-9d15-5faa04038be1

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