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» A Markov Random Field Model for Medical Image Denoising
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VLSM
2005
Springer
15 years 3 months ago
Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
Mariano Rivera, Omar Ocegueda, José L. Marr...
NIPS
2008
14 years 11 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
EMMCVPR
1999
Springer
15 years 1 months ago
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Markus Svensén, Frithjof Kruggel, D. Yves v...
IVC
2006
155views more  IVC 2006»
14 years 9 months ago
A Markov random field image segmentation model for color textured images
Zoltan Kato, Ting-Chuen Pong
CORR
2006
Springer
76views Education» more  CORR 2006»
14 years 9 months ago
Inconsistent parameter estimation in Markov random fields: Benefits in the computation-limited setting
Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and th...
Martin J. Wainwright