A Bayesian belief network is a model of a joint distribution over a finite set of variables, with a DAG structure representing immediate dependencies among the variables. For each...
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
In a recent paper we introduced a modification of the adaptive beamformer orthogonal rejection test (ABORT) for adaptive detection of signals in unknown noise, by supposing under t...
Francesco Bandiera, Olivier Besson, Danilo Orlando...
In this paper, a generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte...
In tradition probability statistics model, speaker verification threshold is instability in different test situations. A novel speaker verification method based on Support Vector ...