DocumentCode
2899410
Title
Image learning classifier system using genetic algorithms
Author
McAulay, Alastair D. ; Oh, Jae Chan
Author_Institution
Dept. of Comput. Sci., Wright State Univ., Dayton, OH, USA
fYear
1989
fDate
22-26 May 1989
Firstpage
705
Abstract
The authors examine aspects of machine learning by classifier systems that use genetic algorithms. In particular, adaptive image learning and classification are considered. Standard classifier systems are not well suited for seeking out multiple goals as is necessary in image learning and classification problems. To improve the performance of standard classifier systems for the image learning task, several modifications are suggested. The modifications result in a far better performance for classifier system on the ImageLearn domain
Keywords
adaptive systems; computerised pattern recognition; computerised picture processing; knowledge representation; learning systems; neural nets; adaptive image learning; classification; genetic algorithms; image learning classifier; Adaptive systems; Computer science; Current measurement; Genetic algorithms; Humans; Image recognition; Learning systems; Machine learning; Particle measurements; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Aerospace and Electronics Conference, 1989. NAECON 1989., Proceedings of the IEEE 1989 National
Conference_Location
Dayton, OH
Type
conf
DOI
10.1109/NAECON.1989.40288
Filename
40288
Link To Document