Automatic design of Cellular Neural Networks by means of Genetic Algorithms: Finding a Feature Detector
Workshop Paper, 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA '94), pp. 189 - 194, December, 1994
Abstract
This paper aims to examine the use of genetic algorithms to optimize sub-systems of cellular neural network architectures. The application at hand is character recognition: the aim is to evolve an optimal feature detector in order to aid a conventional classifier network to generalize across different fonts. To this end, a performance function and a genetic encoding for a feature detector are presented. An experiment is described where an optimal feature detector is indeed found by the genetic algorithm.
BibTeX
@workshop{Dellaert-1994-15998,author = {Frank Dellaert and J. Vandewalle},
title = {Automatic design of Cellular Neural Networks by means of Genetic Algorithms: Finding a Feature Detector},
booktitle = {Proceedings of 3rd IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA '94)},
year = {1994},
month = {December},
pages = {189 - 194},
}
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