Paper
26 March 1986 Learning Techniques Applied To Multi-Font Character Recognition
J.-J. Cannat, Y. Kodratoff
Author Affiliations +
Proceedings Volume 0635, Applications of Artificial Intelligence III; (1986) https://doi.org/10.1117/12.964163
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States
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.
© (1986) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J.-J. Cannat and Y. Kodratoff "Learning Techniques Applied To Multi-Font Character Recognition", Proc. SPIE 0635, Applications of Artificial Intelligence III, (26 March 1986); https://doi.org/10.1117/12.964163
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Cited by 4 scholarly publications.
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KEYWORDS
Taxonomy

Optical character recognition

Artificial intelligence

Scanning transmission electron microscopy

Machine learning

Pattern recognition

Aluminum

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