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.
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