Proceedings Paper
Learning Techniques Applied To Multi-Font Character Recognition| Format | Member Price | Non-Member Price |
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Paper Abstract
In this paper we present the usefulness of symbolic learning techniques for multi-font character recognition. In our already existing models of learning, knowledge is provided and the goal is to find a generalization of given examples, (while for our present model of character recognition knowledge has to be found or rather modified in order to discover a discriminating generalization. An inventive refining of knowledge has allowed to achieve the multi-font character recognition.
Paper Details
Date Published: 26 March 1986
PDF: 11 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964163
Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)
PDF: 11 pages
Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); doi: 10.1117/12.964163
Show Author Affiliations
J.-J. Cannat, Universite De Paris-Sud (France)
Y. Kodratoff, Universite De Paris-Sud (France)
Published in SPIE Proceedings Vol. 0635:
Applications of Artificial Intelligence III
John F. Gilmore, Editor(s)
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