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Novel RAM-based neural networks for object recognition

Howells, Gareth and Fairhurst, Michael and Bisset, David (1996) Novel RAM-based neural networks for object recognition. In: Solomon, Susan S. and Batchelor, Bruce G. and Waltz, Frederick M., eds. Machine Vision Applications, Architectures, and Systems Integration V. Proceedings of SPIE . SPIE, pp. 50-57. ISBN 0-8194-2310-6. (doi:10.1117/12.257276) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:19248)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1117/12.257276

Abstract

This paper introduces a novel networking strategy for RAM-based Neurons which significantly improves the training and recognition performance of such networks whilst maintaining the generalisation capabilities achieved in previous network configurations. A number of different architectures are introduced each using the same underlying principles. Initially, features which are common to all architectures are described illustrating the basis of the underlying paradigm. Three architectures are then introduced illustrating different techniques for employing the paradigm to meet differing performance specifications. The architectures are described in terms of the structure of the neurons they employ. Greater detail of the various training and recognition algorithms employed by the architectures may be found in the referenced papers.

Item Type: Book section
DOI/Identification number: 10.1117/12.257276
Additional information: Conference on Machine Vision Applications, Architectures, and Systems Integration V BOSTON, MA, NOV 18-19, 1996 Soc Photo Opt Instrumentat Engineers
Uncontrolled keywords: neurons; networks architectures; neural networks; detection and tracking algorithms; image classification; object recognition; pattern recognition
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: R.F. Xu
Date Deposited: 04 Jun 2009 16:03 UTC
Last Modified: 16 Nov 2021 09:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/19248 (The current URI for this page, for reference purposes)

University of Kent Author Information

Howells, Gareth.

Creator's ORCID: https://orcid.org/0000-0001-5590-0880
CReDIT Contributor Roles:

Fairhurst, Michael.

Creator's ORCID:
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