In this paper we propose a novel approach for modeling kernels in Radial Basis Function networks. The method provides an extra degree of flexibility to the kernel structure. This ...
We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the un...
Motivated by the success of parts based representations in face detection we have attempted to address some of the problems associated with applying such a philosophy to the task ...
This paper presents a shape representation and a variational framework for the construction of diffeomorphisms that establish "meaningful" correspondences between images...
Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori dist...