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CVPR
2012
IEEE
13 years 2 months ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
ICIP
2008
IEEE
15 years 6 months ago
Correlation Embedding Analysis
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
Yun Fu, Thomas S. Huang
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 7 days ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
AUSAI
2005
Springer
15 years 5 months ago
New Feature Extraction Approaches for Face Recognition
All the traditional PCA-based and LDA-based methods are based on the analysis of vectors. So, it is difficult to evaluate the covariance matrices in such a high-dimensional vector ...
Vo Dinh Minh Nhat, Sungyoung Lee
ICPR
2010
IEEE
15 years 4 months ago
On the Dimensionality Reduction for Sparse Representation Based Face Recognition
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
Lei Zhang, Meng Yang, Zhizhao Feng, David Zhang