Different eigenspace-based approaches have been proposed for the recognition of faces, i.e. eigenface, fisherface and Laplacianface. For fisherfaces, the original image space is reduced to an n-c dimensional subspace in which the standard LDA is carried out, where n is the number of training samples and c is the number of classes. In this paper, we present a spectral analysis of fisherface whic...

ÐThe main motivation of this paper is to propose a new classification and regression method for challenging highdimensional data. The proposed new technique casts classification problems (class labels as output) and regression problems (numeric values as output) into a unified regression problem. This unified view enables classification problems to use numeric information in the output space th...

Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, selfshading and self-occlusion. To address this problem, a multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns from multi-view face images. Kernel Discriminant Analysis is develo...

The aim of this study, based on a prospective analysis, was to evaluate the accuracy of the TEST-yolk buffer enhanced hamster egg penetration test (HEPT) and acrosin activity in discriminating fertile from infertile males as compared with the conventional semen profile. The incidence of spontaneous pregnancies was monitored during a follow-up period ranging between 18-24 months in 62 couples wi...

The discriminating variable (DIVA) test and the selectivity ratio (SR) plot are developed as quantitative tools for revealing the variables in spectral or chromatographic profiles discriminating best between two groups of samples. The SR plot is visually similar to a spectrum or a chromatogram, but with the most intense regions corresponding to the most discriminating variables. Thus, the varia...

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