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• W3100145537 abstract "We revisit the long-standing question of the relation between image appreciation and its statistical properties. We generate two different sets of random images well distributed along three measures of entropic complexity. We run a large-scale survey in which people are asked to sort the images by preference, which reveals maximum appreciation at intermediate entropic complexity. We show that the algorithmic complexity of the coarse-grained images, expected to capture structural complexity while abstracting from high frequency noise, is a good predictor of preferences. Our analysis suggests that there might exist some universal quantitative criteria for aesthetic judgement." @default.
• W3100145537 created "2020-11-23" @default.
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• W3100145537 date "2020-06-15" @default.
• W3100145537 modified "2023-10-16" @default.
• W3100145537 title "Beauty and structural complexity" @default.
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• W3100145537 doi "https://doi.org/10.1103/physrevresearch.2.022058" @default.
• W3100145537 hasPublicationYear "2020" @default.
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