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  3D Object Recognition Using Unsupervised Feature Extraction

Intrator, N., Gold JI, Bülthoff, H., & Edelman, S. (1992). 3D Object Recognition Using Unsupervised Feature Extraction. In Advances in Neural Information Processing Systems 4 (pp. 368-377). San Mateo, CA, USA: Kaufmann.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-EDF4-A Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-EDF5-8
Genre: Conference Paper

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 Creators:
Intrator, N, Author
Gold JI, Bülthoff, HH1, Author           
Edelman, S, Author
Moody, J.E., Editor
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              

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 Abstract: Intrator (1990) proposed a feature extraction method that is related to recent statistical theory (Huber, 1985; Friedman, 1987) and is based on a biologically motivated model of neuronal plasticity (Bienenstock et al., 1982). This method has been recently applied to feature extraction in the context of recognizing 3D objects from single 2D views (Intrator and Gold, 1991). Here we describe experiments designed to analyze the nature of the extracted features, and their relevance to the theory and psychophysics of object recognition.

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 Dates: 1992-04
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISBN: 1-558-60222-4
URI: http://books.nips.cc/nips04.html
BibTex Citekey: 695
 Degree: -

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Title: Fifth Conference on Neural Information Processing Systems - Natural and Synthetic (NIPS 1991)
Place of Event: Denver, CO, USA
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Title: Advances in Neural Information Processing Systems 4
Source Genre: Proceedings
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Publ. Info: San Mateo, CA, USA : Kaufmann
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 368 - 377 Identifier: -