A lattice Gaussian distribution of given mean and covariance matrix is a discrete distribution
supported on a lattice maximizing Shannon's entropy under these mean and covariance …

The Fisher–Rao distance is a measure of dissimilarity between probability distributions,
which, under certain regularity conditions of the statistical model, is up to a scaling factor the …

The Jeffreys divergence is a renown arithmetic symmetrization of the oriented Kullback–
Leibler divergence broadly used in information sciences. Since the Jeffreys divergence …

The change detection of polarimetric synthetic aperture radar (PolSAR) images is a
longstanding and challenging task, not only because of the speckle issue but also due to the …

We present and evaluate a method for kernel regression estimation of fiber orientations and
associated volume fractions for diffusion MR tractography and population-based atlas …

Recent advances in depth imaging sensors provide easy access to the synchronized depth
with color, called RGB-D image. In this paper, we propose an unsupervised method for …

We present a fast and generic algorithm, k-MLE, for learning statistical mixture models using
maximum likelihood estimators. We prove theoretically that k-MLE is dually equivalent to a …

Abstract Relevance-Based Language Models, commonly known as Relevance Models, are
successful approaches to explicitly introduce the concept of relevance in the statistical …

Objectives To develop an algorithm to segment and obtain an estimate of total intracranial
volume (tICV) from computed tomography (CT) images. Materials and methods Thirty-six CT …

Nowadays smartphones get increasingly popular which also attracted hackers. With the
increasing capabilities of such phones, more and more malicious softwares targeting these …