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Cross-cultural comparison of beauty judgments in visual art using machine learning analysis of art attribute predictors among Japanese and German speakers

Abstract In empirical art research, understanding how viewers judge visual artworks as beautiful is often explored through the study of attributes—specific inherent characteristics or artwork features such as color, complexity, and emotional expressiveness. These attributes form the basis for subjec...

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Bibliografische Detailangaben
Hauptverfasser: Jan Mikuni, Blanca T. M. Spee, Gaia Forlani, Helmut Leder, Frank Scharnowski, Koyo Nakamura, Katsumi Watanabe, Hideaki Kawabata, Matthew Pelowski, David Steyrl
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Portfolio 2024-07-01
Schriftenreihe:Scientific Reports
Online-Zugang:https://doi.org/10.1038/s41598-024-65088-z
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