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» Context-specific approximation in probabilistic inference
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SSPR
2004
Springer
14 years 3 months ago
Learning People Movement Model from Multiple Cameras for Behaviour Recognition
Abstract. In surveillance systems for monitoring people behaviour, it is imporant to build systems that can adapt to the signatures of the people tasks and movements in the environ...
Nam Thanh Nguyen, Svetha Venkatesh, Geoff A. W. We...
NIPS
2003
13 years 11 months ago
Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensio...
Leonid Sigal, Michael Isard, Benjamin H. Sigelman,...
UAI
2003
13 years 11 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén
CIDR
2009
157views Algorithms» more  CIDR 2009»
13 years 11 months ago
Capturing Data Uncertainty in High-Volume Stream Processing
We present the design and development of a data stream system that captures data uncertainty from data collection to query processing to final result generation. Our system focuse...
Yanlei Diao, Boduo Li, Anna Liu, Liping Peng, Char...
NECO
2008
170views more  NECO 2008»
13 years 9 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio