Graphical models such as Bayesian Networks (BNs) are being increasingly applied to various computer vision problems. One bottleneck in using BN is that learning the BN model param...
Spatial, temporal and spatio-temporal aggregates over continuous streams of remotely sensed image data build a fundamental operation in many applications in the environmental scie...
Discovering and unlocking the full potential of complex pervasive environments is still approached in application-centric ways. A set of statically deployed applications often deļ...
Geert Vanderhulst, Daniel Schreiber, Kris Luyten, ...
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
Adapting to the network is the key to achieving high performance for communication-intensive applications, including scientiļ¬c computing, data intensive computing, and multicast...