Dynamic Probabilistic Networks (DPNs) are exploited for modelling the temporal relationships among a set of different object temporal events in the scene for a coherent and robust...
Abstract. We describe a probabilistic model, implemented as a dynamic Bayesian network, that can be used to predict nucleosome positioning along a chromosome based on one or more g...
Sheila M. Reynolds, Zhiping Weng, Jeff A. Bilmes, ...
Recent years have seen a proliferation of work on the Semantic Web, an initiative to enable intelligent agents to reason about and utilize World Wide Web content and services. Con...
We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific an...
We present a novel distributed range-free technique called ExPLoIT for estimating geographical location of sensor nodes in mobile sensor networks. ExPLoIT is the rst positioning...
Christophe Baraer, Kaustubh S. Phanse, Johan Nykvi...