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» Dual-Space Linear Discriminant Analysis for Face Recognition
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CVPR
2005
IEEE
14 years 2 months ago
Nonlinear Face Recognition Based on Maximum Average Margin Criterion
This paper proposes a novel nonlinear discriminant analysis method named by Kernerlized Maximum Average Margin Criterion (KMAMC), which has combined the idea of Support Vector Mac...
Baochang Zhang, Xilin Chen, Shiguang Shan, Wen Gao
PR
2002
122views more  PR 2002»
13 years 8 months ago
High-order Fisher's discriminant analysis
This paper introduces a novel nonlinear extension of Fisher's classical linear discriminant analysis (FDA) known as high-order Fisher's discriminant analysis (HOFDA). Th...
Alejandro Sierra
CVPR
2003
IEEE
14 years 10 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum
ICDAR
2009
IEEE
13 years 6 months ago
Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers
In recent years research towards Indian handwritten character recognition is getting increasing attention. Many approaches have been proposed by the researchers towards handwritte...
Umapada Pal, Tetsushi Wakabayashi, Fumitaka Kimura
CVPR
2007
IEEE
14 years 10 months ago
Feature Extraction by Maximizing the Average Neighborhood Margin
A novel algorithm called Average Neighborhood Margin Maximization (ANMM) is proposed for supervised linear feature extraction. For each data point, ANMM aims at pulling the neighb...
Fei Wang, Changshui Zhang