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

Wallis, GM

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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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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-EB46-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0002-8E77-9

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

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Wallis, GM^{1, 2}, Author

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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: Date issued: 1996-08

Publication Status: Issued

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: -