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CIMCA
2005
IEEE
13 years 9 months ago
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model ...
Kazuyuki Tanaka
ICCV
2003
IEEE
14 years 5 months ago
Learning How to Inpaint from Global Image Statistics
Inpainting is the problem of filling-in holes in images. Considerable progress has been made by techniques that use the immediate boundary of the hole and some prior information o...
Anat Levin, Assaf Zomet, Yair Weiss
ECCV
2004
Springer
14 years 5 months ago
A Statistical Model for General Contextual Object Recognition
We consider object recognition as the process of attaching meaningful labels to specific regions of an image, and propose a model that learns spatial relationships between objects....
Peter Carbonetto, Nando de Freitas, Kobus Barnard
ICML
2004
IEEE
14 years 4 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
BCB
2010
140views Bioinformatics» more  BCB 2010»
12 years 10 months ago
Guiding belief propagation using domain knowledge for protein-structure determination
A major bottleneck in high-throughput protein crystallography is producing protein-structure models from an electrondensity map. In previous work, we developed Acmi, a probabilist...
Ameet Soni, Craig A. Bingman, Jude W. Shavlik