Abstract.
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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Received: 31 October 2001, Accepted: 13 December 2002, Published online: 6 June 2003
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Vuurpijl, L., Schomaker, L. & Erp, M.v. Architectures for detecting and solving conflicts: two-stage classification and support vector classifiers. IJDAR 5, 213–223 (2003). https://doi.org/10.1007/s10032-003-0104-1
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DOI: https://doi.org/10.1007/s10032-003-0104-1