Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
This paper discusses a set of modifications regarding the use of the Bayesian Information Criterion (BIC) for the speaker diarization task. We focus on the specific variant of the...
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
A Bayesian marked point process (MPP) model is developed
to detect and count people in crowded scenes. The
model couples a spatial stochastic process governing number
and placem...
In this paper, we propose two approaches for combining geometric information with ICA algorithm to solve permutation problem under the scenario where a rough information about the...