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
fDate :
8/1/1995 12:00:00 AM
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;
Journal_Title :
IEEE Expert
