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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Nature Portfolio
2020
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oai:doaj.org-article:ffa2f7836f054d09ae4e8a005ae4f56a2021-12-02T15:39:26ZCapturing human categorization of natural images by combining deep networks and cognitive models10.1038/s41467-020-18946-z2041-1723https://doaj.org/article/ffa2f7836f054d09ae4e8a005ae4f56a2020-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-18946-zhttps://doaj.org/toc/2041-1723Theories 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.Ruairidh M. BattledayJoshua C. PetersonThomas L. GriffithsNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-14 (2020) |
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Science Q Ruairidh M. Battleday Joshua C. Peterson Thomas L. Griffiths Capturing human categorization of natural images by combining deep networks and cognitive models |
description |
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. |
format |
article |
author |
Ruairidh M. Battleday Joshua C. Peterson Thomas L. Griffiths |
author_facet |
Ruairidh M. Battleday Joshua C. Peterson Thomas L. Griffiths |
author_sort |
Ruairidh M. Battleday |
title |
Capturing human categorization of natural images by combining deep networks and cognitive models |
title_short |
Capturing human categorization of natural images by combining deep networks and cognitive models |
title_full |
Capturing human categorization of natural images by combining deep networks and cognitive models |
title_fullStr |
Capturing human categorization of natural images by combining deep networks and cognitive models |
title_full_unstemmed |
Capturing human categorization of natural images by combining deep networks and cognitive models |
title_sort |
capturing human categorization of natural images by combining deep networks and cognitive models |
publisher |
Nature Portfolio |
publishDate |
2020 |
url |
https://doaj.org/article/ffa2f7836f054d09ae4e8a005ae4f56a |
work_keys_str_mv |
AT ruairidhmbattleday capturinghumancategorizationofnaturalimagesbycombiningdeepnetworksandcognitivemodels AT joshuacpeterson capturinghumancategorizationofnaturalimagesbycombiningdeepnetworksandcognitivemodels AT thomaslgriffiths capturinghumancategorizationofnaturalimagesbycombiningdeepnetworksandcognitivemodels |
_version_ |
1718385969864900608 |