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Proc Natl Acad Sci U S A. 2007 Apr 10;104(15):6424-9. Epub 2007 Apr 2.

A feedforward architecture accounts for rapid categorization.

Author information

1
Center for Biological and Computational Learning, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. serre@mit.edu

Abstract

Primates are remarkably good at recognizing objects. The level of performance of their visual system and its robustness to image degradations still surpasses the best computer vision systems despite decades of engineering effort. In particular, the high accuracy of primates in ultra rapid object categorization and rapid serial visual presentation tasks is remarkable. Given the number of processing stages involved and typical neural latencies, such rapid visual processing is likely to be mostly feedforward. Here we show that a specific implementation of a class of feedforward theories of object recognition (that extend the Hubel and Wiesel simple-to-complex cell hierarchy and account for many anatomical and physiological constraints) can predict the level and the pattern of performance achieved by humans on a rapid masked animal vs. non-animal categorization task.

PMID:
17404214
PMCID:
PMC1847457
DOI:
10.1073/pnas.0700622104
[Indexed for MEDLINE]
Free PMC Article

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