PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Use of Structured Pattern Representations for Combining Classifiers
Raisa Socorro and Luisa Mico
In: Structural, syntactic, and statistical pattern recognition: Joint IAPR International Workshop, 4 Dec - 6 Dec 2008, Orlando, United States.

Abstract

In Pattern Recognition, there are problems where distinct representations can be obtained for the same pattern, and depending on the type of classifiers (statistical or structural) one type of representation is preferred versus the others. In the last years, different approaches to combining classifiers have been proposed to improve the performance of individual classifiers. However, few works investigated the use of structured pattern representations. In this paper combination of classifiers has been applied using tree pattern representation in combination with strings and vectors for a handwritten character classification task. In order to save computational cost, some proposals based on the use of both embedding structured data and refine and filter framework are provided.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:4509
Deposited By:Luisa Mico
Deposited On:13 March 2009