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» Robust Kernel Principal Component Analysis
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WSCG
2004
166views more  WSCG 2004»
13 years 9 months ago
De-noising and Recovering Images Based on Kernel PCA Theory
Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
Pengcheng Xi, Tao Xu
ICIP
2002
IEEE
14 years 9 months ago
Hybrid and parallel face classifier based on artificial neural networks and principal component analysis
We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is ext...
Peter V. Bazanov, Tae-Kyun Kim, Seok-Cheol Kee, Sa...
PR
2007
88views more  PR 2007»
13 years 7 months ago
Robust kernel Isomap
Isomap is one of widely-used low-dimensional embedding methods, where geodesic distances on a weighted graph are incorporated with the classical scaling (metric multidimensional s...
Heeyoul Choi, Seungjin Choi
NIPS
2008
13 years 9 months ago
Supervised Exponential Family Principal Component Analysis via Convex Optimization
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Yuhong Guo
FGR
2004
IEEE
107views Biometrics» more  FGR 2004»
13 years 11 months ago
Intra-Personal Kernel Space for Face Recognition
Intra-personal space modeling proposed by Moghaddam et. al. has been successfully applied in face recognition. In their work the regular principal subspaces are derived from the i...
Shaohua Kevin Zhou, Rama Chellappa, Baback Moghadd...