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» Markov Random Field Models in Computer Vision
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ICML
2005
IEEE
16 years 2 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
TIP
2002
133views more  TIP 2002»
15 years 1 months ago
A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising
Abstract--This paper presents a new wavelet-based image denoising method, which extends a recently emerged "geometrical" Bayesian framework. The new method combines three...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
108
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MICCAI
2002
Springer
16 years 2 months ago
Validation of Tissue Modelization and Classification Techniques in T1-Weighted MR Brain Images
Abstract. We propose a deep study on tissue modelization and classification Techniques on T1-weighted MR images. Three approaches have been taken into account to perform this valid...
Meritxell Bach Cuadra, Bram Platel, Eduardo Solana...
FGR
2011
IEEE
288views Biometrics» more  FGR 2011»
14 years 5 months ago
Hierarchical CRF with product label spaces for parts-based models
— Non-rigid object detection is a challenging open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, humancomput...
Gemma Roig, Xavier Boix Bosch, Fernando De la Torr...
MICCAI
2008
Springer
16 years 2 months ago
MRI Bone Segmentation Using Deformable Models and Shape Priors
Abstract. This paper addresses the problem of automatically segmenting bone structures in low resolution clinical MRI datasets. The novel aspect of the proposed method is the combi...
Jérôme Schmid, Nadia Magnenat-Thalman...