Automatic generation of multipath algorithms in the cellular nonlinear network

Victor M. Preciado; Domingo Guinea; Rodrigo Montufar-Chaveznava

doi:10.1117/12.420936

4 April 2001 Automatic generation of multipath algorithms in the cellular nonlinear network

Victor M. Preciado, Domingo Guinea, Rodrigo Montufar-Chaveznava

Proceedings Volume 4305, Applications of Artificial Neural Networks in Image Processing VI; (2001) https://doi.org/10.1117/12.420936
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

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.

Citation Download Citation

Victor M. Preciado, Domingo Guinea, and Rodrigo Montufar-Chaveznava "Automatic generation of multipath algorithms in the cellular nonlinear network", Proc. SPIE 4305, Applications of Artificial Neural Networks in Image Processing VI, (4 April 2001); https://doi.org/10.1117/12.420936

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