In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
We address document image classification by visual appearance. An image is represented by a variable-length list of visually salient features. A hierarchical Bayesian network is ...
Tracking interacting human body parts from a single two-dimensional view is difficult due to occlusion, ambiguity and spatio-temporal discontinuities. We present a Bayesian networ...
—In this paper, we investigate how packet delays and losses affect the quality of target tracking. Specifically, we use Bayesian information of the posterior distribution of tar...
Wei Wei, Ting He, Chatschik Bisdikian, Dennis Goec...