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» On Combining Classifiers
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ICMCS
2005
IEEE
90views Multimedia» more  ICMCS 2005»
14 years 3 months ago
Integrating co-training and recognition for text detection
Training a good text detector requires a large amount of labeled data, which can be very expensive to obtain. Cotraining has been shown to be a powerful semi-supervised learning t...
Wen Wu, Datong Chen, Jie Yang
EMO
2006
Springer
120views Optimization» more  EMO 2006»
14 years 8 hour ago
Rule Induction for Classification Using Multi-objective Genetic Programming
Multi-objective metaheuristics have previously been applied to partial classification, where the objective is to produce simple, easy to understand rules that describe subsets of a...
Alan P. Reynolds, Beatriz de la Iglesia
NAACL
2007
13 years 11 months ago
Hybrid Models for Semantic Classification of Chinese Unknown Words
This paper addresses the problem of classifying Chinese unknown words into fine-grained semantic categories defined in a Chinese thesaurus. We describe three novel knowledge-based...
Xiaofei Lu
ICIP
2003
IEEE
14 years 3 months ago
ICA and Gabor representation for facial expression recognition
Two hybrid systems for classifying seven categories of human facial expression are proposed. The £rst system combines independent component analysis (ICA) and support vector mach...
Ioan Buciu, Constantine Kotropoulos, Ioannis Pitas
ICML
2000
IEEE
14 years 11 months ago
Solving the Multiple-Instance Problem: A Lazy Learning Approach
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...
Jun Wang, Jean-Daniel Zucker