The main idea of this paper is to integrate the non-contextual support vector machines (SVM) classifiers with Markov random fields (MRF) approach to develop a contextual framework for monitoring of agricultural land cover. To this end, the SVM and MRF approaches were integrated to exploit both spectral and spatial contextual information in the image for more accurate classification of remote se...

This paper describes a method for building a compact online Markov random field (MRF) recognizer for large handwritten Japanese character set using structured dictionary representation and vector quantization (VQ) technique. The method splits character patterns into radicals, whose models by MRF are shared by different character classes such that a character model is constructed from the consti...

Real world systems typically feature a variety of different dependency types and topologies that complicate model selection for probabilistic graphical models. We introduce the ensemble-offorests model, a generalization of the ensembleof-trees model of Meilă and Jaakkola (2006). Our model enables structure learning of Markov random fields (MRF) with multiple connected components and arbitrary p...

We propose a Markov Random Field (MRF) formulation for the intensity-based N-view 2D-3D registration problem. The transformation aligning the 3D volume to the 2D views is estimated by iterative updates obtained by discrete optimization of the proposed MRF model. We employ a pairwise MRF model with a fully connected graph in which the nodes represent the parameter updates and the edges encode th...

texture image analysis is one of the most important working realms of image processing in medical sciences and industry. up to present, different approaches have been proposed for segmentation of texture images. in this paper, we offered unsupervised texture image segmentation based on markov random field (mrf) model. first, we used gabor filter with different parameters’ (frequency, orientatio...

This research aims to determine the effect of bank size (SIZE), profitability (ROA), efficiency (EFF), non-performing finance (NPF), interest (INTR), and inflation (INFL) on profit loss sharing (PLS) financing (equity financing), sale-purchase (SP) (debt financing) Islamic banks in Indonesia. Furthermore, monthly data June 2014 July 2020 was used. The autoregressive distributed lag (ARDL) method used sho...

We present a new general Bayesian formulation for simultaneously restoring and segmenting piecewise smooth images. This implies estimation of the associated parameters of the classes within an image, the class label for each image pixel and the number of classes. The intensity image is modelled by parametric models based on regularized networks. The method fits the regions (or classes) with com...

-The most important task in digital image processing is image segmentation. This paper put forward an unique image segmentation algorithm that make use of a Markov Random Field (MRF) hybrid with biologically inspired technique Bacteria Foraging Optimization Algorithm (BFOA) for Brain Magnetic Resonance Images The proposed new algorithm works on the image pixel data and a region/neighborhood map...

In this paper we demonstrate a new method for Bayesian image segmentation, with specific application to Synthetic Aperture Radar (SAR) imagery, and we compare its performance to conventional Bayesian segmentation methods. Segmentation can be an important feature extraction technique in recognition problems, especially when we can incorporate prior information to improve the segmentation. Markov...

Abstract This study proposes a novel integrated material recovery and waste-to-hydrogen concept in view of enhancing resource efficiency minimising environmental impact. A comprehensive techno-economic evaluation is conducted on an system consisting facility (MRF) gasification rejected materials for hydrogen production (Gasification-H2). Valorising these through Gasification-H2 can potentially ...