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BMCBI
2008
135views more  BMCBI 2008»
13 years 9 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
KDD
2012
ACM
183views Data Mining» more  KDD 2012»
11 years 11 months ago
Mining discriminative components with low-rank and sparsity constraints for face recognition
This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
Qiang Zhang, Baoxin Li
JMM2
2006
110views more  JMM2 2006»
13 years 8 months ago
Two-Stage PCA Extracts Spatiotemporal Features for Gait Recognition
We propose a technique for gait recognition from motion capture data based on two successive stages of principal component analysis (PCA) on kinematic data. The first stage of PCA ...
Sandhitsu R. Das, Robert C. Wilson, Maciej T. Laza...
ICMLA
2007
13 years 10 months ago
Scalable optimal linear representation for face and object recognition
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
Yiming Wu, Xiuwen Liu, Washington Mio
CVPR
2004
IEEE
14 years 10 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang