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Proceedings Paper

Automatic generation of multipath algorithms in the cellular nonlinear network
Author(s): Victor M. Preciado; Domingo Guinea; Rodrigo Montufar-Chaveznava
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Paper Abstract

The objective of this work is to generate a learning machine capable of find solutions for complex image processing task by Cellular Neural Network (CNN's). First a general machine for automatic analog algorithm design independent of the problem to solve is created, this is accomplished through an evolutionary strategy that is an extension of genetic programming. Second, this work introduces a suite of sub- mechanisms that increase the power of genetic programming and contribute to reduce the enormous space search for producing a plentiful search. Some concepts in this section are related with AI theory, in such a way that in this work we are in the intersection field of AI and Image Processing by CNN.

Paper Details

Date Published: 4 April 2001
PDF: 11 pages
Proc. SPIE 4305, Applications of Artificial Neural Networks in Image Processing VI, (4 April 2001); doi: 10.1117/12.420936
Show Author Affiliations
Victor M. Preciado, Univ. de Exremadura (Spain)
Domingo Guinea, Consejo Superior de Investigaciones Cientificas (Spain)
Rodrigo Montufar-Chaveznava, Consejo Superior de Investigaciones Cientificas (Spain)


Published in SPIE Proceedings Vol. 4305:
Applications of Artificial Neural Networks in Image Processing VI
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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