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CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
PAMI
2008
119views more  PAMI 2008»
13 years 7 months ago
Triplet Markov Fields for the Classification of Complex Structure Data
We address the issue of classifying complex data. We focus on three main sources of complexity, namely, the high dimensionality of the observed data, the dependencies between these...
Juliette Blanchet, Florence Forbes
NIPS
2001
13 years 9 months ago
Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field
Reaching movements require the brain to generate motor commands that rely on an internal model of the task's dynamics. Here we consider the errors that subjects make early in...
O. Donchin, Reza Shadmehr
ICDAR
2011
IEEE
12 years 7 months ago
On-line Handwritten Japanese Characters Recognition Using a MRF Model with Parameter Optimization by CRF
— This paper describes a Markov random field (MRF) model with weighting parameters optimized by conditional random field (CRF) for on-line recognition of handwritten Japanese cha...
Bilan Zhu, Masaki Nakagawa
UAI
2004
13 years 9 months ago
From Fields to Trees
We present new MCMC algorithms for computing the posterior distributions and expectations of the unknown variables in undirected graphical models with regular structure. For demon...
Firas Hamze, Nando de Freitas