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Classifier design plays a paramount role in pattern recognition. Previously, we set the problem in the framework of function approximation, wherein a classifier is assumed to be an element of a reproducing kernel Hilbert space continuously defined on the pattern feature space, and adopted orthogonal projection criteria for classifier design. In practice, subspaces spanned by features of different...
Due its possibilities in security systems and robotics, face recognition is one of the most researched areas within the biometric field. In a common scenario from real life face recognition problem, the dimension in the sample space is larger than the number of training samples per class. This is known as the “small sample size problem”. Discriminative Common Vectors (DCV) technique has been used...
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