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    Exploring Human Cognition Using Large Image Databases. 
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    Exploring Human Cognition Using Large Image Databases.

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    Accepted version (15.28Mb)
    Volume
    8
    Pagination
    569 - 588
    DOI
    10.1111/tops.12209
    Journal
    Top Cogn Sci
    Issue
    3
    Metadata
    Show full item record
    Abstract
    Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories.
    Authors
    Griffiths, TL; Abbott, JT; Hsu, AS
    URI
    http://qmro.qmul.ac.uk/xmlui/handle/123456789/15004
    Collections
    • Theoretical Computer Science Group [25]
    Language
    eng
    Licence information
    “Original publication is available at http://onlinelibrary.wiley.com/doi/10.1111/tops.12209/full
    Copyright statements
    Copyright © 2016 Cognitive Science Society, Inc.
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