Capturing human categorization of natural images by combining deep networks and cognitive models

Theories of human categorization have traditionally been evaluated in the context of simple, low-dimensional stimuli. In this work, the authors use a large dataset of human behavior over 10,000 natural images to re-evaluate these theories, revealing interesting differences from previous results.

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Detalles Bibliográficos
Autores principales: Ruairidh M. Battleday, Joshua C. Peterson, Thomas L. Griffiths
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/ffa2f7836f054d09ae4e8a005ae4f56a
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Descripción
Sumario:Theories of human categorization have traditionally been evaluated in the context of simple, low-dimensional stimuli. In this work, the authors use a large dataset of human behavior over 10,000 natural images to re-evaluate these theories, revealing interesting differences from previous results.