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» Iterative Improvement of Neural Classifiers
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SETN
2004
Springer
15 years 3 months ago
A Meta-classifier Approach for Medical Diagnosis
Abstract. Single classifiers, such as Neural Networks, Support Vector Machines, Decision Trees and other, can be used to perform classification of data for relatively simple proble...
George L. Tsirogiannis, Dimitrios S. Frossyniotis,...
TSMC
2008
177views more  TSMC 2008»
14 years 8 months ago
Adaptive Critic Learning Techniques for Engine Torque and Air-Fuel Ratio Control
A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning con...
Derong Liu, Hossein Javaherian, Olesia Kovalenko, ...
IDEAL
2004
Springer
15 years 3 months ago
In-Situ Learning in Multi-net Systems
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
Matthew C. Casey, Khurshid Ahmad
CVPR
2010
IEEE
14 years 7 months ago
P-N learning: Bootstrapping binary classifiers by structural constraints
This paper shows that the performance of a binary classifier can be significantly improved by the processing of structured unlabeled data, i.e. data are structured if knowing the ...
Zdenek Kalal, Jiri Matas, Krystian Mikolajczyk
ICONIP
2010
14 years 7 months ago
Multi-view Gender Classification Using Hierarchical Classifiers Structure
In this paper, we propose a hierarchical classifier structure for gender classification based on facial images by reducing the complexity of the original problem. In the proposed f...
Tian-Xiang Wu, Bao-Liang Lu