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  Three-Dimensional Object Recognition Using an Unsupervised Neural Network: Understanding the Distinguishing Features

Intrator, N., Gold, J., Bülthoff, H., & Edelman, S. (1991). Three-Dimensional Object Recognition Using an Unsupervised Neural Network: Understanding the Distinguishing Features. In Y. Feldman, & A. Bruckstein (Eds.), 8th Israeli Conference on AICV (pp. 113-123). Amsterdam, The Netherlands: Elsevier.

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 Creators:
Intrator, N, Author
Gold, JI, Author
Bülthoff, HH1, Author           
Edelman, S, Author           
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1External Organizations, ou_persistent22              

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 Abstract: A novel method for feature extraction has been applied to a problem of three-dimensional object recognition (Intrator and Gold, 1991). The method is related to recent statistical theory (Huber, 1985; Friedman, 1987) and is derived from a biologically motivated computational theory (Bienenstock, Cooper and Munro, 1982). Results of an initial study replicating recent psychophysical experiments (Bulthoff and Edelman 1991) demonstrated the utility of the proposed method for feature extraction. We describe further 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: 1991
 Publication Status: Published in print
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 Rev. Type: -
 Identifiers: BibTex Citekey: 722
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Title: 8th Israeli Conference on AICV
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Title: 8th Israeli Conference on AICV
Source Genre: Proceedings
 Creator(s):
Feldman, Y, Editor
Bruckstein, A, Editor
Affiliations:
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Publ. Info: Amsterdam, The Netherlands : Elsevier
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 113 - 123 Identifier: -