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» Combining SVM Classifiers for Handwritten Digit Recognition
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DAS
2006
Springer
13 years 11 months ago
Segmentation of On-Line Handwritten Japanese Text Using SVM for Improving Text Recognition
Abstract. This paper describes a method of producing segmentation point candidates for on-line handwritten Japanese text by a support vector machine (SVM) to improve text recogniti...
Bilan Zhu, Junko Tokuno, Masaki Nakagawa
NIPS
2001
13 years 8 months ago
Categorization by Learning and Combining Object Parts
We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
ICPR
2000
IEEE
14 years 8 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...
IJCAI
2007
13 years 9 months ago
Parametric Kernels for Sequence Data Analysis
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
Young-In Shin, Donald S. Fussell
ICDAR
2003
IEEE
14 years 23 days ago
Comparison of Genetic Algorithm and Sequential Search Methods for Classifier Subset Selection
Classifier subset selection (CSS) from a large ensemble is an effective way to design multiple classifier systems (MCSs). Given a validation dataset and a selection criterion, the...
Hongwei Hao, Cheng-Lin Liu, Hiroshi Sako