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» Support Vector Machines Applied to Face Recognition
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ICNC
2005
Springer
14 years 1 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
ICB
2007
Springer
121views Biometrics» more  ICB 2007»
13 years 12 months ago
SVDD-Based Illumination Compensation for Face Recognition
Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to comp...
Sang-Woong Lee, Seong-Whan Lee
CVPR
2005
IEEE
14 years 8 months ago
A Framework of 2D Fisher Discriminant Analysis: Application to Face Recognition with Small Number of Training Samples
A novel framework called 2D Fisher Discriminant Analysis (2D-FDA) is proposed to deal with the Small Sample Size (SSS) problem in conventional One-Dimensional Linear Discriminan...
Hui Kong, Lei Wang, Eam Khwang Teoh, Jian-Gang Wan...
IJCNN
2006
IEEE
14 years 2 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
ICMLA
2009
13 years 5 months ago
Text Classification Methodologies Applied to Micro-Text in Military Chat
We propose methods to classify lines of military chat, or posts, which contain items of interest. We evaluated several current text categorization and feature selection methodologi...
Kevin Dela Rosa, Jeffrey Ellen