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  How neurons learn to associate 2D-views in invariant object recognition

Wallis, G.(1996). How neurons learn to associate 2D-views in invariant object recognition (37). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

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MPIK-TR-37.pdf (Publisher version), 134KB
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 Creators:
Wallis, GM1, 2, Author              
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: A local learning rule is shown to be able to account for the association of images together on the basis of temporal order rather than spatial configuration, as described in single cell recording results published by Miyashita (1988). Possible reasons for requiring such learning are then given in the context of invariant object recognition.

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 Dates: 1996-08
 Publication Status: Published in print
 Pages: 6
 Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics
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 Identifiers: Report Nr.: 37
BibTex Citekey: 1501
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Title: Technical Report of the Max Planck Institute for Biological Cybernetics
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Pages: - Volume / Issue: 37 Sequence Number: - Start / End Page: - Identifier: -