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Temporal constraints on visual learning: a computational model.

Abstract:

Given a constant stream of perceptual stimuli, how can the underlying invariances associated with a given input be learned? One approach consists of using generic truths about the spatiotemporal structure of the physical world as constraints on the types of quantities learned. The learning methodology employed here embodies one such truth: that perceptually salient properties (such as stereo disparity) tend to vary smoothly over time. Unfortunately, the units of an artificial neural network t...

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Publisher copy:
10.1068/p2860

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Institution:
University of Oxford
Division:
MSD
Department:
Physiology Anatomy & Genetics
Role:
Author
Journal:
Perception More from this journal
Volume:
28
Issue:
9
Pages:
1089-1104
Publication date:
1999-01-01
DOI:
EISSN:
1468-4233
ISSN:
0301-0066
Language:
English
Keywords:
Pubs id:
pubs:382899
UUID:
uuid:682cf6bf-89e8-454a-b66e-b2d02247d3f4
Local pid:
pubs:382899
Source identifiers:
382899
Deposit date:
2013-11-16

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