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GLVLSI
2006
IEEE
193views VLSI» more  GLVLSI 2006»
14 years 5 months ago
Optimizing noise-immune nanoscale circuits using principles of Markov random fields
As CMOS devices and operating voltages are scaled down, noise and defective devices will impact the reliability of digital circuits. Probabilistic computing compatible with CMOS o...
Kundan Nepal, R. Iris Bahar, Joseph L. Mundy, Will...
VLSM
2005
Springer
14 years 4 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...
ICPR
2000
IEEE
14 years 3 months ago
Nonparametric Markov Random Field Model Analysis of the MeasTex Test Suite
This paper looks at the nonparametric, multiscale, Markov Random Field (MRF) model and its application in classifying the MeasTex Test Suite. The MeasTex Test Suite is a standard ...
Rupert Paget, I. Dennis Longstaff
CORR
2006
Springer
76views Education» more  CORR 2006»
13 years 11 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
PAMI
2010
396views more  PAMI 2010»
13 years 9 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu