18 search results - page 1 / 4 » Null Space-based Kernel Fisher Discriminant Analysis for Fac... |
FGR
2004
IEEE
13 years 9 months ago
2004
IEEE
The null space-based LDA takes full advantage of the null space while the other methods remove the null space. It proves to be optimal in performance. From the theoretical analysi...
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 ...
ICB
2007
Springer
13 years 9 months ago
2007
Springer
The symmetrical decomposition is a powerful method to extract features for image recognition. It reveals the significant discriminative information from the mirror image of symmetr...
ACII
2005
Springer
13 years 7 months ago
2005
Springer
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Kernel Fisher Discriminant Analysis (KFDA) has achieved great success in pattern recognition recently. However, the training process of KFDA is too time consuming (even intractabl...