Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...
This paper proposes a method of finding a discriminative linear transformation that enhances the data's degree of conformance to the compactness hypothesis and its inverse. Th...
—Emerging applications of computer vision and pattern recognition in mobile devices and networked computing require the development of resourcelimited algorithms. Linear classifi...
Discriminant feature extraction plays a fundamental role in pattern recognition. In this paper, we propose the Linear Laplacian Discrimination (LLD) algorithm for discriminant fea...
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...