Recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. It enables efficient fusion of different types of features. Ba...
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filterin...
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga...
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...