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ICMLA
2008
13 years 9 months ago
An Improved Generalized Discriminant Analysis for Large-Scale Data Set
In order to overcome the computation and storage problem for large-scale data set, an efficient iterative method of Generalized Discriminant Analysis is proposed. Because sample v...
Weiya Shi, Yue-Fei Guo, Cheng Jin, Xiangyang Xue
TSMC
2008
182views more  TSMC 2008»
13 years 7 months ago
Incremental Linear Discriminant Analysis for Face Recognition
Abstract--Dimensionality reduction methods have been successfully employed for face recognition. Among the various dimensionality reduction algorithms, linear (Fisher) discriminant...
Haitao Zhao, Pong Chi Yuen
SDM
2007
SIAM
182views Data Mining» more  SDM 2007»
13 years 9 months ago
Distance Preserving Dimension Reduction for Manifold Learning
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
Hyunsoo Kim, Haesun Park, Hongyuan Zha
FGR
2008
IEEE
246views Biometrics» more  FGR 2008»
13 years 8 months ago
Discriminant analysis for perceptionally comparable classes
Traditional discriminate analysis treats all the involved classes equally in the computation of the between-class scatter matrix. However, we find that for many vision tasks, the...
Bingpeng Ma, Shiguang Shan, Xilin Chen, Wen Gao
IJHPCA
2008
104views more  IJHPCA 2008»
13 years 7 months ago
Low-Complexity Principal Component Analysis for Hyperspectral Image Compression
Principal component analysis (PCA) is an effective tool for spectral decorrelation of hyperspectral imagery, and PCA-based spectral transforms have been employed successfully in co...
Qian Du, James E. Fowler