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Models of visual categorization
Author(s) -
Serre Thomas
Publication year - 2016
Publication title -
wiley interdisciplinary reviews: cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.526
H-Index - 49
eISSN - 1939-5086
pISSN - 1939-5078
DOI - 10.1002/wcs.1385
Subject(s) - categorization , perception , psychophysics , cognitive science , visual perception , computational model , computer science , visual processing , bridging (networking) , vision science , cognitive psychology , psychology , artificial intelligence , data science , neuroscience , computer network
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. WIREs Cogn Sci 2016, 7:197–213. doi: 10.1002/wcs.1385 This article is categorized under: Psychology > Perception and Psychophysics Neuroscience > Computation