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ICPR
2006
IEEE
14 years 8 months ago
Type-2 Fuzzy Markov Random Fields to Handwritten Character Recognition
This paper integrates Markov random fields (MRFs) with type-2 fuzzy sets (T2 FSs) referred to as T2 FMRFs, which can handle the fuzziness of the labeling space as well as the rand...
Jia Zeng, Zhi-Qiang Liu
PR
2008
84views more  PR 2008»
13 years 7 months ago
Practical background estimation for mosaic blending with patch-based Markov random fields
In this paper, we present a new background estimation algorithm which effectively represents both background and foreground. The problem is formulated with a labeling problem over...
Dae Woong Kim, Ki-Sang Hong
ICA
2007
Springer
13 years 11 months ago
Conjugate Gamma Markov Random Fields for Modelling Nonstationary Sources
In modelling nonstationary sources, one possible strategy is to define a latent process of strictly positive variables to model variations in second order statistics of the underly...
Ali Taylan Cemgil, Onur Dikmen
ICPR
2002
IEEE
14 years 8 months ago
Face Detection and Synthesis Using Markov Random Field Models
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Sarat C. Dass, Anil K. Jain, Xiaoguang Lu
CEC
2005
IEEE
14 years 1 months ago
Incorporating a Metropolis method in a distribution estimation using Markov random field algorithm
Abstract- Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)...
Siddhartha Shakya, John A. W. McCall, Deryck F. Br...