We demonstrate how to leverage a system’s capability for allto-all communication to achieve an exponential speed-up of local algorithms despite bandwidth and memory restrictions...
— In this paper we consider a probabilistic approach to the problem of localization in wireless sensor networks and propose a distributed algorithm that helps unknown nodes to de...
Abstract. In the frequency allocation problem we are given a cellular telephone network whose geographical coverage area is divided into cells where phone calls are serviced by fre...
We have proposed a complete system for text detection and localization in gray scale scene images. A boosting framework integrating feature and weak classifier selection based on...
Modern Bayesian Network learning algorithms are timeefficient, scalable and produce high-quality models; these algorithms feature prominently in decision support model development...