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» Learning a Restricted Bayesian Network for Object Detection
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ISMIS
2005
Springer
14 years 1 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni
ICCV
2007
IEEE
14 years 9 months ago
Learning Higher-order Transition Models in Medium-scale Camera Networks
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
Ryan Farrell, David S. Doermann, Larry S. Davis
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
14 years 2 months ago
Probabilistic categorization of kitchen objects in table settings with a composite sensor
— In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our fra...
Zoltan Csaba Marton, Radu Bogdan Rusu, Dominik Jai...
IWANN
2009
Springer
14 years 2 months ago
Optimising Machine-Learning-Based Fault Prediction in Foundry Production
Abstract. Microshrinkages are known as probably the most difficult defects to avoid in high-precision foundry. The presence of this failure renders the casting invalid, with the su...
Igor Santos, Javier Nieves, Yoseba K. Penya, Pablo...
CVPR
2008
IEEE
14 years 9 months ago
Trajectory analysis and semantic region modeling using a nonparametric Bayesian model
We propose a novel nonparametric Bayesian model, Dual Hierarchical Dirichlet Processes (Dual-HDP), for trajectory analysis and semantic region modeling in surveillance settings, i...
Xiaogang Wang, Keng Teck Ma, Gee Wah Ng, W. Eric L...