Abstract
This work presents a pattern recognition system that is able to detect ambiguous patterns and explain its answers. The system consists of a set of parallel Support Vector Machine (SVM) classifiers, each one dedicated to a representative feature extracted from the input, followed by an analysing module based on a bayesian strategy in charge of defining the system answer. We apply the system to the recognition of handwritten numerals. Experiments were carried out on the MNIST database, which is generally accepted as one of the standards in most of the literature in the field.
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Seijas, L., Segura, E. (2009). Detection of Ambiguous Patterns Using SVMs: Application to Handwritten Numeral Recognition. In: Jiang, X., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2009. Lecture Notes in Computer Science, vol 5702. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03767-2_102
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DOI: https://doi.org/10.1007/978-3-642-03767-2_102
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-03767-2
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