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FGR
2008
IEEE
214views Biometrics» more  FGR 2008»
13 years 11 months ago
Normalized LDA for semi-supervised learning
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Bin Fan, Zhen Lei, Stan Z. Li
ICTAI
2008
IEEE
13 years 11 months ago
Face Recognition Using a Color Subspace LDA Approach
This paper delves into the problem of face recognition using color as an important cue in improving the accuracy of recognition. To perform recognition of color images, we use the...
Mani Thomas, Chandra Kambhamettu, Senthil Kumar
ICPR
2008
IEEE
13 years 11 months ago
Face recognition using Complete Fuzzy LDA
In this paper, we propose a novel method for feature extraction and recognition, namely, Complete Fuzzy LDA (CFLDA). CFLDA combines the complete LDA and fuzzy set theory. CFLDA re...
Wankou Yang, Hui Yan, Jianguo Wang, Jingyu Yang
ICNC
2005
Springer
13 years 10 months ago
Line-Based PCA and LDA Approaches for Face Recognition
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) techniques are important and well-developed area of image recognition and to date many linear discriminati...
Vo Dinh Minh Nhat, Sungyoung Lee
CVPR
2004
IEEE
14 years 6 months ago
Dual-Space Linear Discriminant Analysis for Face Recognition
Linear Discriminant Analysis (LDA) is popular feature extraction technique for face recognition. However, it often suffers from the small sample size problem when dealing with the...
Xiaogang Wang, Xiaoou Tang