Abstract
Visual categorization refers to our ability to organize objects and visual scenes into discrete categories. It is an essential skill as it allows us to distinguish friend from foe or edible versus poisonous food. Understanding how the visual system categorizes objects and scenes is a challenge because it requires bridging the gap between different levels of understanding-from the level of neural circuits and neural networks to the level of information processing and, ultimately, behavior. Computational models have become powerful tools for integrating knowledge across these levels of analysis. We review recent progress in our understanding of the computational mechanisms underlying visual categorization and discuss some of the remaining challenges.
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