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» Face recognition using mixtures of principal components
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ICASSP
2008
IEEE
14 years 2 months ago
A study of using locality preserving projections for feature extraction in speech recognition
This paper presents a new approach to feature analysis in automatic speech recognition (ASR) based on locality preserving projections (LPP). LPP is a manifold based dimensionality...
Yun Tang, Richard Rose
ICIP
2008
IEEE
14 years 2 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
MM
2004
ACM
248views Multimedia» more  MM 2004»
14 years 1 months ago
Incremental semi-supervised subspace learning for image retrieval
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
Xiaofei He
PAMI
2008
153views more  PAMI 2008»
13 years 7 months ago
Correlation Metric for Generalized Feature Extraction
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Yun Fu, Shuicheng Yan, Thomas S. Huang
TIFS
2008
129views more  TIFS 2008»
13 years 7 months ago
On Empirical Recognition Capacity of Biometric Systems Under Global PCA and ICA Encoding
Performance of biometric-based recognition systems depends on various factors: database quality, image preprocessing, encoding techniques, etc. Given a biometric database and a se...
Natalia A. Schmid, Francesco Nicolo