Kernel based methods have been of wide concern in the field of machine learning. This paper proposes a novel Gabor-Kernel Fisher analysis method (G-EKFM) for face recognition, whi...
A successful face recognition system calculates similarity of face images based on the activation of multiscale and multiorientation Gabor kernels, but without utilizing any stati...
Peter Kalocsai, Christoph von der Malsburg, J. Hor...
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...
Fisher linear discriminant analysis (FLDA) based on variance ratio is compared with scatter linear discriminant (SLDA) analysis based on determinant ratio. It is shown that each o...
Miroslaw Bober, Krzysztof Kucharski, Wladyslaw Ska...
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...