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PAMI
2006
183views more  PAMI 2006»
13 years 7 months ago
A Model-Based Approach for Estimating Human 3D Poses in Static Images
Estimating human body poses in static images is important for many image understanding applications including semantic content extraction and image database query and retrieval. Th...
Mun Wai Lee, Isaac Cohen
PRL
2000
182views more  PRL 2000»
13 years 7 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
NECO
2002
145views more  NECO 2002»
13 years 7 months ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen
SIGMETRICS
2002
ACM
115views Hardware» more  SIGMETRICS 2002»
13 years 7 months ago
Maximum likelihood network topology identification from edge-based unicast measurements
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
JCST
2010
139views more  JCST 2010»
13 years 6 months ago
Dirichlet Process Gaussian Mixture Models: Choice of the Base Distribution
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Dilan Görür, Carl Edward Rasmussen