We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
The study of collaborative, distributed, real-time sensor networks is an emerging research area. Such networks are expected to play an essential role in a number of applications su...
Peshala V. Pahalawatta, Dejan Depalov, Thrasyvoulo...
This paper presents a fully automatic white matter lesion (WML) segmentation method, based on local features determined by combining multiple MR acquisition protocols, including T...
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...