Research Repository

Feature extraction and classification by genetic programming

Oechsle, O and Clark, AF (2008) Feature extraction and classification by genetic programming. In: UNSPECIFIED, ? - ?.

Full text not available from this repository.

Abstract

This paper explores the use of genetic programming for constructing vision systems. A two-stage approach is used, with separate evolution of the feature extraction and classification stages. The strategy taken for the classifier is to evolve a set of partial solutions, each of which works for a single class. It is found that this approach is significantly faster than conventional genetic programming, and frequently results in a better classifier. The effectiveness of the approach is explored on three classification problems. © 2008 Springer-Verlag Berlin Heidelberg.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 06 Mar 2012 12:43
Last Modified: 05 Feb 2019 19:15
URI: http://repository.essex.ac.uk/id/eprint/2263

Actions (login required)

View Item View Item