DocumentCode
2540982
Title
Design and training of multilayer discrete time cellular neural networks for antipersonnel mine detection using genetic algorithms
Author
López, E. ; Balsi, M. ; Vilarino, D.L. ; Cabello, D.
Author_Institution
Dept. of Electron. & Comput. Sci., Santiago de Compostela Univ., Spain
fYear
2000
fDate
2000
Firstpage
363
Lastpage
368
Abstract
In this work we present a novel strategy for the simultaneous design and training of multilayer discrete-time cellular neural networks. This methodology is applied to the detection of surface-laid antipersonnel mines in infrared imaging. The procedure is based on the application of genetic algorithms for both network design and learning task
Keywords
buried object detection; cellular neural nets; civil engineering computing; genetic algorithms; infrared imaging; learning (artificial intelligence); military computing; multilayer perceptrons; GA; IR imaging; antipersonnel mine detection; genetic algorithms; infrared imaging; multilayer discrete-time cellular neural networks; Algorithm design and analysis; Cellular neural networks; Computer science; Genetic algorithms; Infrared imaging; Landmine detection; Multi-layer neural network; Nonhomogeneous media; Temperature sensors; Thermodynamics;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
Conference_Location
Catania
Print_ISBN
0-7803-6344-2
Type
conf
DOI
10.1109/CNNA.2000.877356
Filename
877356
Link To Document