356 search results - page 6 / 72 » Solving the Small Sample Size Problem of LDA |
ICIP
2002
IEEE
14 years 9 months ago
2002
IEEE
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
PR
2008
13 years 7 months ago
2008
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
SETN
2010
Springer
13 years 11 months ago
2010
Springer
The optimal sizing of a small autonomous hybrid power system can be a very challenging task, due to the large number of design settings and the uncertainty in key parameters. This ...
IJPRAI
2006
13 years 7 months ago
2006
Linear Discriminant Analysis (LDA) is a popular feature extraction technique in statistical pattern recognition. However, it often suffers from the small sample size problem when ...
AUSAI
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) prob...