We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
The Distributed Object Group Framework(DOGF) we constructed supports the grouping of distributed objects that are required for distributed application. From the DOGF, we manage dis...
Distributed Open Inventor is an extension to the popular Open Inventor toolkit for interactive 3D graphics. The toolkit is extended with the concept of a distributed shared scene ...
Gerd Hesina, Dieter Schmalstieg, Anton L. Fuhrmann...
Over the last few years, target tracking in wireless sensor networks has become a topic of particular interest. This paper presents a tracking system intended for deployment in di...
Evangelos B. Mazomenos, Jeffrey S. Reeve, Neil M. ...
In this paper we present decomposable priors, a family of priors over structure and parameters of tree belief nets for which Bayesian learning with complete observations is tracta...