This paper presents the uDSSP ("micro DSSP") programming model which simplifies the development of distributed sensor network applications that make use of complex in-net...
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
This paper considers the problem of estimating the power breakdowns for the main appliances inside a building using a small number of power meters and the knowledge of the ON/OFF ...
Sensor networks have opened new horizons and opportunities for a variety of environmental monitoring, surveillance and healthcare applications. One of the major tasks of sensor ne...