313 search results - page 24 / 63 » Boosting with Diverse Base Classifiers |
118
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ICDAR
2003
IEEE
15 years 7 months ago
2003
IEEE
The use of artificial outputs generated by a classifier simulator has recently emerged as a new trend to provide an underlying evaluation of classifier combination methods. In thi...
137
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AVBPA
2003
Springer
15 years 5 months ago
2003
Springer
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
125
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ESWA
2006
15 years 1 months ago
2006
In this paper we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to ...
ICPR
2006
IEEE
16 years 2 months ago
2006
IEEE
In this paper we present a unsupervised learning based approach for sub-pixel motion estimation. The novelty of this work is the learning based method itself which tries to learn ...
105
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KDD
2009
ACM
16 years 2 months ago
2009
ACM
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...