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AAAI
2006
13 years 6 months ago
On Combining Multiple Classifiers Using an Evidential Approach
Combining multiple classifiers via combining schemes or meta-learners has led to substantial improvements in many classification problems. One of the challenging tasks is to choos...
Yaxin Bi, Sally I. McClean, Terry J. Anderson
IPMU
2010
Springer
13 years 7 months ago
Evidential Combination of Multiple HMM Classifiers for Multi-script Handwritting Recognition
In this work, we focus on an improvement of a multi-script handwritting recognition system using a HMM based classifiers combination. The improvement relies on the use of Dempster-...
Yousri Kessentini, Thomas Burger, Thierry Paquet
FGR
2004
IEEE
200views Biometrics» more  FGR 2004»
13 years 9 months ago
Using Random Subspace to Combine Multiple Features for Face Recognition
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
Xiaogang Wang, Xiaoou Tang
FLAIRS
2003
13 years 6 months ago
Low Level Fusion of Imagery Based on Dempster-Shafer Theory
An approach to fuse multiple images based on Dempster-Shafer evidential reasoning is proposed in this article. Dempster-Shafer theory provides a complete framework for combining w...
Xiaohui Yuan, Jian Zhang 0007, Xiaojing Yuan, Bill...
ESANN
2004
13 years 6 months ago
Online policy adaptation for ensemble classifiers
Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of usin...
Christos Dimitrakakis, Samy Bengio