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» A Bayesian approach for image segmentation with shape priors
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PRL
2000
182views more  PRL 2000»
13 years 8 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
CVPR
2005
IEEE
14 years 10 months ago
Shape Regularized Active Contour Using Iterative Global Search and Local Optimization
Recently, nonlinear shape models have been shown to improve the robustness and flexibility of segmentation. In this paper, we propose Shape Regularized Active Contour (ShRAC) that...
Tianli Yu, Jiebo Luo, Narendra Ahuja
ECCV
2006
Springer
14 years 10 months ago
Smooth Image Segmentation by Nonparametric Bayesian Inference
A nonparametric Bayesian model for histogram clustering is proposed to automatically determine the number of segments when Markov Random Field constraints enforce smooth class assi...
Peter Orbanz, Joachim M. Buhmann
ICIP
2005
IEEE
14 years 10 months ago
A weight-adaptive dynamic model for shape segmentation
Physically based dynamic models are able to describe variable shapes without prior training. Their behaviour to find an object is intuitive, which facilitates corrections of false...
Klaus D. Tönnies, Peter Benedix
TIP
2010
127views more  TIP 2010»
13 years 7 months ago
Bayesian Compressive Sensing Using Laplace Priors
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...