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» Generalized Discriminant Analysis Using a Kernel Approach
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CVPR
2001
IEEE
14 years 10 months ago
Constructing Facial Identity Surfaces in a Nonlinear Discriminating Space
Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, selfshadi...
Yongmin Li, Shaogang Gong, Heather M. Liddell
FLAIRS
2004
13 years 10 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
IJCNLP
2005
Springer
14 years 2 months ago
Using Multiple Discriminant Analysis Approach for Linear Text Segmentation
Research on linear text segmentation has been an on-going focus in NLP for the last decade, and it has great potential for a wide range of applications such as document summarizati...
Jingbo Zhu, Na Ye, Xinzhi Chang, Wenliang Chen, Be...
WACV
2002
IEEE
14 years 1 months ago
An Experimental Evaluation of Linear and Kernel-Based Methods for Face Recognition
In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
CVPR
2009
IEEE
15 years 3 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin