The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...
The design of an optimal Bayesian classifier for multiple features is dependent on the estimation of multidimensional joint probability density functions and therefore requires a ...
In this paper we present a fusion technique for Support Vector Machine (SVM) scores, obtained after a dimension reduction with Bilateralprojection-based Two-Dimensional Principal C...
Information fusion has, in the form of multiple classifier systems, long been a successful tool in pattern recognition applications. It is also becoming increasingly popular in bio...
Torsten Rohlfing, Adolf Pfefferbaum, Edith V. Sull...
This paper presents a novel method for the classification of images that combines information extracted from the images and contextual information. The main hypothesis is that con...