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ICPR
2004
IEEE
15 years 10 months ago
Principal Component Analysis for Online Handwritten Character Recognition
In this paper, Principal Component Analysis (PCA) is applied to the problem of Online Handwritten Character Recognition in the Tamil script. The input is a temporally ordered sequ...
A. G. Ramakrishnan, Sriganesh Madhvanath, V. Deepu
IJHPCA
2008
104views more  IJHPCA 2008»
14 years 9 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
ICCV
2011
IEEE
13 years 9 months ago
Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
Vikram Appia, Balaji Ganapathy, Tracy Faber, Antho...
JMLR
2010
155views more  JMLR 2010»
14 years 4 months ago
Structured Sparse Principal Component Analysis
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
Rodolphe Jenatton, Guillaume Obozinski, Francis Ba...
ICCV
2001
IEEE
15 years 11 months ago
Robust Principal Component Analysis for Computer Vision
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
Fernando De la Torre, Michael J. Black