DocumentCode
896036
Title
Generating pattern-recognition systems using evolutionary learning
Author
Tamburino, Louis A. ; Zmuda, Mithael A. ; Rizki, Mateen M.
Author_Institution
Avionic Directorate, Wright Lab., Wright-Patterson AFB, OH, USA
Volume
10
Issue
4
fYear
1995
fDate
8/1/1995 12:00:00 AM
Firstpage
63
Lastpage
68
Abstract
The E-morph learning algorithm combines a number of learning algorithms-genetic, evolutionary programming, clustering-into a hybrid learning system for solving multiclass pattern-recognition problems. Our work also shows that a randomly generated pool of primitive detectors, rather than manually coded features, can be enhanced and assembled into effective solution sets
Keywords
genetic algorithms; image recognition; learning (artificial intelligence); pattern recognition; E-morph learning algorithm; clustering algorithm; evolutionary learning; evolutionary programming algorithm; genetic algorithm; hybrid learning system; multiclass pattern-recognition problems; pattern-recognition systems; primitive detectors; Character generation; Character recognition; Data structures; Detectors; Genetic algorithms; Genetic mutations; Image recognition; Navigation; Pattern recognition; Phase measurement;
fLanguage
English
Journal_Title
IEEE Expert
Publisher
ieee
ISSN
0885-9000
Type
jour
DOI
10.1109/64.403962
Filename
403962
Link To Document