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» Graph model selection using maximum likelihood
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NIPS
2004
13 years 10 months ago
Expectation Consistent Free Energies for Approximate Inference
We propose a novel a framework for deriving approximations for intractable probabilistic models. This framework is based on a free energy (negative log marginal likelihood) and ca...
Manfred Opper, Ole Winther
IJCV
2008
201views more  IJCV 2008»
13 years 9 months ago
Probabilistic Fusion of Stereo with Color and Contrast for Bi-Layer Segmentation
This paper describes two algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from colour/contr...
Vladimir Kolmogorov, Antonio Criminisi, Andrew Bla...
SSPR
2004
Springer
14 years 2 months ago
Adaptive Context for a Discrete Universal Denoiser
Abstract. Statistical analysis of spatially uniform signal contexts allows Discrete Universal Denoiser (DUDE) to effectively correct signal errors caused by a discrete symmetric me...
Georgy L. Gimel'farb
CVPR
2005
IEEE
14 years 11 months ago
Object Detection Using 2D Spatial Ordering Constraints
Object detection is challenging partly due to the limited discriminative power of local feature descriptors. We amend this limitation by incorporating spatial constraints among ne...
Yan Li, Yanghai Tsin, Yakup Genc, Takeo Kanade
ICMLA
2009
13 years 6 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz