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» Inference for Order Reduction in Markov Random Fields
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CORR
2008
Springer
167views Education» more  CORR 2008»
13 years 7 months ago
Energy Scaling Laws for Distributed Inference in Random Networks
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...
ICPR
2002
IEEE
14 years 8 months ago
Illumination Invariant Segmentation of Spatio-Temporal Images by Spatio-Temporal Markov Random Field Model
For many years, object tracking in images has suffered from the problems of occlusions and illumination effects. In order to resolve occlusion problems, we have been proposing the...
Shunsuke Kamijo, Katsushi Ikeuchi, Masao Sakauchi
ICCV
2007
IEEE
14 years 9 months ago
LogCut - Efficient Graph Cut Optimization for Markov Random Fields
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...
Victor S. Lempitsky, Carsten Rother, Andrew Blake
JMIV
2002
122views more  JMIV 2002»
13 years 7 months ago
Markov Random Field Modeling in Median Pyramidal Transform Domain for Denoising Applications
We consider a median pyramidal transform for denoising applications. Traditional techniques of pyramidal denoising are similar to those in wavelet-based methods. In order to remove...
Ilya Gluhovsky, Vladimir P. Melnik, Ilya Shmulevic...
ICASSP
2010
IEEE
13 years 5 months ago
Learning in Gaussian Markov random fields
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Thomas J. Riedl, Andrew C. Singer, Jun Won Choi