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A Unifying Framework for Invariant Pattern Recognition

A Unifying Framework for Invariant Pattern Recognition
A Unifying Framework for Invariant Pattern Recognition
We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Network. We show that many standard invariance techniques can be viewed as GRNs, including the DFT power spectrum, higher order neural network and fast translation-invariant transform.
Invariant pattern recognition, Group theory, Discrete Fourier transform, Fast translation-invariant transform, Invariant neural networks, Higher-order networks
1415-1422
Wood, J.
65587872-7126-469a-851a-d60195d39058
Shawe-Taylor, J.
c32d0ee4-b422-491f-8c28-78663851d6db
Wood, J.
65587872-7126-469a-851a-d60195d39058
Shawe-Taylor, J.
c32d0ee4-b422-491f-8c28-78663851d6db

Wood, J. and Shawe-Taylor, J. (1996) A Unifying Framework for Invariant Pattern Recognition. Pattern Recognition Letters, 17 (0167-8), 1415-1422.

Record type: Article

Abstract

We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Network. We show that many standard invariance techniques can be viewed as GRNs, including the DFT power spectrum, higher order neural network and fast translation-invariant transform.

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More information

Published date: December 1996
Keywords: Invariant pattern recognition, Group theory, Discrete Fourier transform, Fast translation-invariant transform, Invariant neural networks, Higher-order networks
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 250475
URI: http://eprints.soton.ac.uk/id/eprint/250475
PURE UUID: f1fea9ed-1aa1-45dc-8e62-7aaa42a5a3e3

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Date deposited: 16 Mar 2004
Last modified: 08 Jan 2022 14:40

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Contributors

Author: J. Wood
Author: J. Shawe-Taylor

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