ICONIP
2010
2010
A New Framework for Small Sample Size Face Recognition Based on Weighted Multiple Decision Templates
13 years 3 months ago
In this paper a holistic method and a local method based on decision template ensemble are investigated. In addition by combining both methods, a new hybrid method for boosting the...
PAA
2007
13 years 4 months ago
2007
Feature selection methods are often used to determine a small set of informative features that guarantee good classification results. Such procedures usually consist of two compon...
BMCBI
2010
13 years 5 months ago
2010
Background: Before conducting a microarray experiment, one important issue that needs to be determined is the number of arrays required in order to have adequate power to identify...
FGR
2004
IEEE
13 years 8 months ago
2004
IEEE
LDA is a popular subspace based face recognition approach. However, it often suffers from the small sample size problem. When dealing with the high dimensional face data, the LDA ...
ECCV
2004
Springer
13 years 10 months ago
2004
Springer
The null space of the within-class scatter matrix is found to express most discriminative information for the small sample size problem (SSSP). The null space-based LDA takes full ...
ICMCS
2006
IEEE
13 years 11 months ago
2006
IEEE
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
ICPR
2008
IEEE
13 years 11 months ago
2008
IEEE
Two Dimensional Linear Discriminant Analysis (2DLDA) has received much interest in recent years. However, 2DLDA could make pairwise distances between any two classes become signi...
ICB
2009
Springer
13 years 11 months ago
2009
Springer
The small sample size problem and the difficulty in determining the optimal reduced dimension limit the application of subspace learning methods in the gait recognition domain. To...
ICPR
2002
IEEE
14 years 6 months ago
2002
IEEE
The small sample size problem is often encountered in pattern recognition. It results in the singularity of the within-class scatter matrix Sw in Linear Discriminant Analysis (LDA...
ECCV
2006
Springer
14 years 7 months ago
2006
Springer
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...