Architectures for detecting and solving conflicts: two-stage classification and support vector classifiers
SourceInternational Journal on Document Analysis and Recognition, 5, 4 [Spec Is, (2002), pp. 213-223
Article / Letter to editor
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SW OZ DCC AI
SW OZ NICI KI
International Journal on Document Analysis and Recognition
iss. 4 [Spec Is
SubjectCognitive artificial intelligence
In the majority of cases, a properly trained classifier or ensemble of classifiers may yield acceptable recognition results. However, in some cases, recognition will fail due to typical conflicts that are encountered, like the confusion between [A] and [H] or [U] and [V]. In this paper, two architectures for the recognition of handwritten text are described. The key issue for each of these systems is to detect the event of a possible conflict and subsequently attempt to solve that particular problem. Both systems exploit a two-stage classification method. In the event that the first-stage classifiers are not certain about the result, the second-stage system engages a set of support vector classifiers for refining the output hypothesis.
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