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

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Wallis,  GM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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MPIK-TR-37.pdf
(Publisher version), 134KB

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Citation

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


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-EB46-2
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.