334 search results - page 15 / 67 » Diagonal principal component analysis for face recognition |
SIBGRAPI
2005
IEEE
14 years 1 months ago
2005
IEEE
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recog...
FGR
1998
IEEE
13 years 12 months ago
1998
IEEE
The performance of a local feature based system, using Gabor-filters, and a global template matching based system, using a combination of PCA (Principal Component Analysis) and LD...
JCP
2008
13 years 7 months ago
2008
kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
TNN
2008
13 years 7 months ago
2008
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
ICDM
2006
IEEE
14 years 1 months ago
2006
IEEE
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...