Abstract
In this paper we discuss the capability of the cellular programming approach to produce non-uniform cellular automata performing two-dimensional pattern classification. More precisely, after an introduction to the evolutionary cellular automata model, we describe a general approach suitable for designing cellular classifiers. The approach is based on a set of non-uniform cellular automata performing specific classification tasks, which have been designed by means of a cellular evolutionary algorithm.
The proposed approach is discussed together with some preliminary results obtained on a benchmark data set consisting of car-plate digits.
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© 1998 Springer-Verlag Berlin Heidelberg
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Adorni, G., Bergenti, F., Cagnoni, S. (1998). A cellular-programming approach to pattern classification. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds) Genetic Programming. EuroGP 1998. Lecture Notes in Computer Science, vol 1391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055934
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DOI: https://doi.org/10.1007/BFb0055934
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