نتایج جستجو برای: fuzzy markov random field
تعداد نتایج: 1184507 فیلتر نتایج به سال:
Based upon previous studies on laws of large numbers for fuzzy, random, fuzzy random and random fuzzy variables, We go further to explore weak law of large numbers(WLLN) for hybrid variables comprising fuzzy random variables and random fuzzy variables. we mainly prove Chebyshev WLLN, Poisson WLLN, Bernoulli WLLN, Markov WLLN and Khintchin WLLN for hybrid variables based on chance measure.
A modified version of MRFFCM (Markov Random Field Fuzzy C means) based SAR (Synthetic aperture Radar) image change detection method is proposed in this paper. It involves three steps: Difference Image (DI) generation by using Gauss-log ratio operator, speckle noise reduction by SRAD (Speckle Reducing Anisotropic Diffusion), and the detection of changed regions by using MRFFCM. The proposed meth...
Automatically recognizing the e-learning activities is an important task for improving the online learning process. Probabilistic graphical models such as Hidden Markov Models and Conditional Random Fields have been successfully used in order to identify a web user activity. For such models, the sequences of observation are crucial for training and inference processes. Despite the efficiency of...
A novel modeling technique for automatic control purposes is discussed. A fuzzy Markov system is proposed to describe both determined and random behavior of complex dynamic plants. The main advantage is its high computational speed. Another benefit of this method is its flexibility and applicability to both linear and nonlinear systems. A controlled Markov chain represents a fuzzy system with a...
-Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic approaches. Most of these techniques are not suitable for noisy environments. Some works have been done using the Markov Random Field (MRF) model which is robust to noise, but is computationally involved. N...
In this article we propose a modification to the HMRF-EM framework applied to image segmentation. To do so, we introduce a new model for the neighborhood energy function of the Hidden Markov Random Fields model based on the Hidden Markov Model formalism. With this new energy model, we aim at (1) avoiding the use of a key parameter chosen empirically on which the results of the current models ar...
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