Fluorescence molecular tomography (FMT) allows in vivo localization and quantification of fluorescence biodistributions in whole animals. The ill-posed nature of the tomographic re...
Damon Hyde, Eric L. Miller, Dana H. Brooks, Vasili...
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
Abstract--Reconstruction algorithms for fluorescence tomography have to address two crucial issues : (i) the ill-posedness of the reconstruction problem, (ii) the large scale of nu...
Algorithms based on the minimization of the Total Variation are prevalent in computer vision. They are used in a variety of applications such as image denoising, compressive sensi...
In this paper, we examine the problem of overcomplete representations and provide new insights into the problem of stable recovery of sparse solutions in noisy environments. We es...