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» Markov Random Fields with Efficient Approximations
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PAMI
2002
108views more  PAMI 2002»
13 years 7 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
EMNLP
2009
13 years 5 months ago
Graphical Models over Multiple Strings
We study graphical modeling in the case of stringvalued random variables. Whereas a weighted finite-state transducer can model the probabilistic relationship between two strings, ...
Markus Dreyer, Jason Eisner
CORR
2011
Springer
188views Education» more  CORR 2011»
13 years 2 months ago
Planar Cycle Covering Graphs
We describe a new variational lower-bound on the minimum energy configuration of a planar binary Markov Random Field (MRF). Our method is based on adding auxiliary nodes to every...
Julian Yarkony, Alexander T. Ihler, Charless C. Fo...
IPMI
2005
Springer
14 years 8 months ago
From Spatial Regularization to Anatomical Priors in fMRI Analysis
In this paper, we study Markov Random Fields as spatial smoothing priors in fMRI detection. Relatively high noise in fMRI images presents a serious challenge for the detection algo...
Wanmei Ou, Polina Golland
CVPR
2009
IEEE
15 years 2 months ago
Continuous Maximal Flows and Wulff Shapes: Application to MRFs
Convex and continuous energy formulations for low level vision problems enable efficient search procedures for the corresponding globally optimal solutions. In this work we exte...
Christopher Zach (UNC Chapel Hill), Marc Niethamme...