Automatic self-configuration of a novel multiple-expert classifier using a genetic algorithm

Rahman, Ahmad Fuad Rezaur and Fairhurst, Michael (1999) Automatic self-configuration of a novel multiple-expert classifier using a genetic algorithm. In: Seventh International Conference on Image Processing And Its Applications, 1999. IEEE, pp. 57-61. ISBN 0-85296-717-9. (doi:10.1049/cp:19990281) (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:16510)

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/10.1049/cp:19990281

Abstract

A novel self-configurable multiple expert classifier is introduced. A genetic algorithm has been employed to automate the process of optimisation in terms of structural configuration. Application of this concept of self-configuration has produced very promising results in recognising a database of machine printed characters by the proposed multiple expert configuration.

Item Type:	Book section
DOI/Identification number:	10.1049/cp:19990281
Additional information:	Issue: 465; Proceedings Paper
Uncontrolled keywords:	automatic self-configuration; multiple-expert classifier; genetic algorithm; optimisation; structural configuration; machine printed characters database; multiple expert configuration
Subjects:	Q Science > Q Science (General) > Q335 Artificial intelligence Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK5101 Telecommunications > TK5103.59 Optical communications
Divisions:	Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User:	F.D. Zabet
Date Deposited:	17 Apr 2009 18:52 UTC
Last Modified:	05 Nov 2024 09:51 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/16510 (The current URI for this page, for reference purposes)

University of Kent Author Information

Fairhurst, Michael.

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