Architectures for detecting and solving conflicts: two-stage classification and support vector classifiers
Publication year
2002Source
International Journal on Document Analysis and Recognition, 5, 4 [Spec Is, (2002), pp. 213-223ISSN
Publication type
Article / Letter to editor

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Organization
SW OZ DCC AI
Former Organization
SW OZ NICI KI
Journal title
International Journal on Document Analysis and Recognition
Volume
vol. 5
Issue
iss. 4 [Spec Is
Page start
p. 213
Page end
p. 223
Subject
Cognitive artificial intelligenceAbstract
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.
This item appears in the following Collection(s)
- Academic publications [227881]
- Faculty of Social Sciences [28470]
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