When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
This work presents a class of unidirectional lifting-based wavelet transforms for an arbitrary communication graph in a wireless sensor network. These transforms are unidirectiona...
We propose a new method for recovering a 3-D object shape from an image sequence. In order to recover high-resolution relative depth without using the complex Markov random field...
Unattended Wireless Sensor Networks (UWSNs) are composed of many small resource-constrained devices and operate autonomously, gathering data which is periodically collected by a v...
Roberto Di Pietro, Di Ma, Claudio Soriente, Gene T...
In this paper, we present a graph-theoretic framework for provisioning overlay network based multimedia distribution services to a diverse set of receivers. Considering resource l...