Title :
Machine learning and genetic algorithms: an application to character recognition
Author :
Bontempi, Bruno ; Marcelli, Angelo
Author_Institution :
Dipartimento di Inf. e Sistemistica, Naples Univ., Italy
Abstract :
An application of genetic-based machine learning to the problem of online character recognition is presented. Genetic learners are essentially inductive rule-based systems which exploit an analogy with biological populations evolving under the laws of natural selection. Experimental results are also reported
Keywords :
character recognition; genetic algorithms; knowledge based systems; learning (artificial intelligence); learning systems; real-time systems; genetic algorithms; genetic learning; inductive rule-based systems; machine learning; online character recognition; Character recognition; Deformable models; Feature extraction; Genetic algorithms; Handwriting recognition; Machine learning; Nervous system; Optical character recognition software; Robustness; Writing;
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
DOI :
10.1109/ICSMC.1994.400195
