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Computational Neuroscience of Vision$
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Edmund Rolls and Gustavo Deco

Print publication date: 2001

Print ISBN-13: 9780198524885

Published to Oxford Scholarship Online: March 2012

DOI: 10.1093/acprof:oso/9780198524885.001.0001

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Models of invariant object recognition

Models of invariant object recognition

Chapter:
(p.243) 8 Models of invariant object recognition
Source:
Computational Neuroscience of Vision
Author(s):

Edmund T. Rolls

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198524885.003.0008

This chapter examines neural network approaches to invariant pattern recognition. It describes different computational approaches that have been taken both in artificial vision systems and as suggestions for how the brain performs invariant object recognition, including feature spaces, structural descriptions, and syntactic pattern recognition. The chapter evaluates the hypotheses about the computational mechanisms in the visual cortex for object recognition and discusses the computational issues associated with the feature hierarchy approach to invariant object recognition.

Keywords:   invariant pattern recognition, neural network, computational approaches, artificial vision system, feature spaces, syntactic pattern recognition, visual cortex, object recognition

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