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» Constructing Visual Models with a Latent Space Approach
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CVPR
2007
IEEE
15 years 7 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen
SCALESPACE
2007
Springer
15 years 7 months ago
Towards Segmentation Based on a Shape Prior Manifold
Incorporating shape priors in image segmentation has become a key problem in computer vision. Most existing work is limited to a linearized shape space with small deformation modes...
Patrick Etyngier, Renaud Keriven, Jean-Philippe Po...
IJCAI
2001
15 years 2 months ago
Approximate inference for first-order probabilistic languages
A new, general approach is described for approximate inference in first-order probabilistic languages, using Markov chain Monte Carlo (MCMC) techniques in the space of concrete po...
Hanna Pasula, Stuart J. Russell
ISBI
2009
IEEE
15 years 8 months ago
Improving M/EEG Source Localization with an Inter-Condition Sparse Prior
The inverse problem with distributed dipoles models in M/EEG is strongly ill-posed requiring to set priors on the solution. Most common priors are based on a convenient ℓ2 norm....
Alexandre Gramfort, Matthieu Kowalski
ACSD
2003
IEEE
105views Hardware» more  ACSD 2003»
15 years 5 months ago
Detecting State Coding Conflicts in STG Unfoldings Using SAT
Abstract. The behaviour of asynchronous circuits is often described by Signal Transition Graphs (STGs), which are Petri nets whose transitions are interpreted as rising and falling...
Victor Khomenko, Maciej Koutny, Alexandre Yakovlev