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» Combining Simple Discriminators for Object Discrimination
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ICASSP
2010
IEEE
13 years 9 months ago
Boosted binary features for noise-robust speaker verification
The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a nov...
Anindya Roy, Mathew Magimai-Doss, Sébastien...
CVPR
2005
IEEE
14 years 2 months ago
Nonlinear Face Recognition Based on Maximum Average Margin Criterion
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
Baochang Zhang, Xilin Chen, Shiguang Shan, Wen Gao
SSPR
2000
Springer
14 years 12 days ago
The Role of Combining Rules in Bagging and Boosting
To improve weak classifiers bagging and boosting could be used. These techniques are based on combining classifiers. Usually, a simple majority vote or a weighted majority vote are...
Marina Skurichina, Robert P. W. Duin
CVPR
2006
IEEE
14 years 10 months ago
Spatial Divide and Conquer with Motion Cues for Tracking through Clutter
Tracking can be considered a two-class classification problem between the foreground object and its surrounding background. Feature selection to better discriminate object from ba...
Zhaozheng Yin, Robert T. Collins
ICML
2009
IEEE
14 years 9 months ago
Learning non-redundant codebooks for classifying complex objects
Codebook-based representations are widely employed in the classification of complex objects such as images and documents. Most previous codebook-based methods construct a single c...
Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Di...