DocumentCode
2692725
Title
A genetic algorithm for training image classification neural networks
Author
Zhang, Ching ; Wang, Fangju
Author_Institution
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume
3
fYear
1994
fDate
2-5 Oct 1994
Firstpage
2242
Abstract
Neural networks are becoming effective tools for digital image classification. They have advantages including simple and flexible structures and higher tolerance to errors. The major drawbacks which limit neural networks for practical applications include slow training phase and divergence of training. In this research, a new method has been developed to address the drawbacks. This method is based on genetic algorithms
Keywords
genetic algorithms; image classification; learning (artificial intelligence); neural nets; digital image; genetic algorithm; image classification; learning; neural networks; training phase; Computer networks; Design engineering; Digital images; Flexible structures; Genetic algorithms; Image classification; Information science; Neural networks; Pattern classification; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location
San Antonio, TX
Print_ISBN
0-7803-2129-4
Type
conf
DOI
10.1109/ICSMC.1994.400198
Filename
400198
Link To Document