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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| Main Authors: | , , |
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| Format: | article |
| Language: | EN |
| Published: |
Nature Portfolio
2020
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| Subjects: | |
| Online Access: | https://doaj.org/article/ffa2f7836f054d09ae4e8a005ae4f56a |
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| Summary: | 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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