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CVPR
2008
IEEE
14 years 10 months ago
Learning Bayesian Networks with qualitative constraints
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...
Yan Tong, Qiang Ji
ICANN
2009
Springer
14 years 1 months ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
COMPSEC
2004
91views more  COMPSEC 2004»
13 years 8 months ago
Predicting the intrusion intentions by observing system call sequences
Identifying the intentions or attempts of the monitored agents through observations is very vital in computer network security. In this paper, a plan recognition method for predict...
Li Feng, Xiaohong Guan, Sangang Guo, Yan Gao, Pein...
ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 7 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
ICMLA
2007
13 years 10 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...