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» Generalized Discriminant Analysis Using a Kernel Approach
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ICPR
2006
IEEE
14 years 2 months ago
Fast Linear Discriminant Analysis Using Binary Bases
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...
Feng Tang, Hai Tao
CVPR
2006
IEEE
14 years 10 months ago
Shape-Based Approach to Robust Image Segmentation using Kernel PCA
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum
ICPR
2008
IEEE
14 years 3 months ago
Object recognition using graph spectral invariants
Graph structures have been proved important in high level-vision since they can be used to represent structural and relational arrangements of objects in a scene. One of the probl...
Bai Xiao, Richard C. Wilson, Edwin R. Hancock
BMCBI
2010
154views more  BMCBI 2010»
13 years 8 months ago
Candidate gene prioritization by network analysis of differential expression using machine learning approaches
Background: Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available...
Daniela Nitsch, Joana P. Gonçalves, Fabian ...
AMFG
2005
IEEE
152views Biometrics» more  AMFG 2005»
14 years 2 months ago
Regularization of LDA for Face Recognition: A Post-processing Approach
When applied to high-dimensional classification task such as face recognition, linear discriminant analysis (LDA) can extract two kinds of discriminant vectors, those in the null s...
Wangmeng Zuo, Kuanquan Wang, David Zhang, Jian Yan...