Litcius/Paper detail

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features

Kiyohito Iigaya, Sanghyun Yi, Iman A. Wahle, Koranis Tanwisuth, John P. O’Doherty

2021Nature Human Behaviour146 citationsDOIOpen Access PDF

Topics & Concepts

Convolutional neural networkPreferenceArtificial intelligenceSet (abstract data type)Object (grammar)Computer scienceImage (mathematics)Cognitive neuroscience of visual object recognitionVisual perceptionPattern recognition (psychology)Feature (linguistics)Value (mathematics)Cognitive psychologyPsychologyMathematicsMachine learningPerceptionStatisticsNeurosciencePhilosophyProgramming languageLinguisticsAesthetic Perception and AnalysisVisual Attention and Saliency DetectionMultisensory perception and integration
Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features | Litcius