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- Rahman Farnoosh, Morteza Ebrahimi
- Applied Mathematics and Computation
- 2008

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will… (More)

Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image was… (More)

Abstract. Recently stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. Also image segmentation means to divide one picture into different types of classes or regions, for example a picture of geometric shapes has some classes with different colors such as… (More)

SUMMARY We investigate a Bayesian method for the segmentation of muscle fibre images. The images are reasonably well approximated by a Dirichlet tessellation, and so we use a deformable template model based on Voronoi polygons to represent the segmented image. We consider various prior distributions for the parameters and suggest an appropriate likelihood.… (More)

- C C Taylor, I L Dryden, R Farnoosh
- Biometrics
- 2001

We propose modeling a nearly regular point pattern by a generalized Neyman-Scott process in which the offspring are Gaussian perturbations from a regular mean configuration. The mean configuration of interest is an equilateral grid, but our results can be used for any stationary regular grid. The case of uniformly distributed points is first studied as a… (More)

- Rahman Farnoosh, Amirhossein Sobhani, Hamidreza Rezazadeh, Mohammad Hossein Beheshti
- Computers & Mathematics with Applications
- 2015

- Rahman Farnoosh, Mohamadtaghi Rahimi, Pranesh Kumar
- FUZZ-IEEE
- 2016

A model is used to describe a digitized image and as a basis for segmentation. Following the Bayesian paradigm the mathematical form for the likelihood and the posterior distribution are obtained, where the prior distribution is based on a tessellation derived from an inhibition point process. We introduce two algorithms for estimating the posterior mode: a… (More)

- Rahman Farnoosh, Morteza Ebrahimi
- Kybernetes
- 2009

In this paper, we deal with the ridge-type estimator for fuzzy nonlinear regression models using fuzzy numbers and Gaussian basis functions. Shrinkage regularization methods are used in linear and nonlinear regression models to yield consistent estimators. Here, we propose a weighted ridge penalty on a fuzzy nonlinear regression model, then select the… (More)