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» Generalized Discriminant Analysis Using a Kernel Approach
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115
Voted
CVPR
2001
IEEE
16 years 3 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
146
Voted
FLAIRS
2004
15 years 3 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
139
Voted
IJCNLP
2005
Springer
15 years 7 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
15 years 6 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
16 years 9 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