We propose a general approach to discriminant feature extraction and fusion, built on an optimal feature transformation for discriminant analysis [6]. Our experiments indicate tha...
Current texture analysis methods enable good discrimination but are computationally too expensive for applications which require high frame rates. This occurs because they use red...
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable ...
Sergio Valcarcel Macua, Pavle Belanovic, Santiago ...