Automatic CNN multi-template tree generation

Abstract

We deal with the cellular neural network (CNN) research in the development of analogic algorithms that combine single templates to perform complex image processing. The results can be very useful for pattern recognition in industrial and robotic applications. This work presents a general methodology for the automatic generation of analogic algorithms by means of a genetic search. A genetic algorithm for generating multi-template trees, a concept derived from the AI field, is applied to the automatic generation of analogic algorithms based on both the genetic-evolutionary search and heuristic approaches.