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Dissertations / Theses on the topic 'Markov Random Field Model'

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Published: 3 June 2025

Last updated: 31 July 2025

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1

Barker, Simon A. "Image segmentation using Markov random field models." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/272037.

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2

Barker, S. A. "Unsupervised image segmentation using Markov Random Field models." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596368.

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The development of a fully unsupervised algorithm to achieve image segmentation is the central theme of this dissertation. Existing literature falls short of such a goal providing many algorithms capable of solving a subset of this highly challenging problem. Unsupervised segmentation is the process of identifying and locating the constituent regions of an observed image, while having no prior knowledge of the number of regions. The problem can be formulated in a Bayesian framework and through the use of an assumed model unsupervised segmentation can be posed as a problem of optimisation. This

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3

Kasetkasem, Teerasit. "Image analysis methods based on Markov random field models." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

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4

Islam, Mofakharul University of Ballarat. "Unsupervised Color Image Segmentation Using Markov Random Fields Model." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12827.

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We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

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5

Frondana, Iara Moreira. "Model selection for discrete Markov random fields on graphs." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-02022018-151123/.

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In this thesis we propose to use a penalized maximum conditional likelihood criterion to estimate the graph of a general discrete Markov random field. We prove the almost sure convergence of the estimator of the graph in the case of a finite or countable infinite set of variables. Our method requires minimal assumptions on the probability distribution and contrary to other approaches in the literature, the usual positivity condition is not needed. We present several examples with a finite set of vertices and study the performance of the estimator on simulated data from theses examples. We also

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6

Islam, Mofakharul. "Unsupervised color image segmentation using Markov Random Fields Model." Thesis, University of Ballarat, 2008. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/53709.

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We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

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7

Islam, Mofakharul. "Unsupervised color image segmentation using Markov Random Fields Model." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15694.

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We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

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8

Manggala, Putra. "On Markov random field models for spatial data: towards a practitioners toolbox." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114270.

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In the era of big data, data sets have been growing very large, and interest for algorithms and computation framework that handle such large scales is increasing. The number of computing cores per chip has also increased. Instead of developing ingenious ways of speeding up convergences and obtaining better approximations for a smaller subclass of the problems, it is interesting to simply "throw more cores" at exact algorithms and get a speed-up which scales accordingly. This allows practitioners who are not specialists to use the algorithms more efficiently. The MapReduce framework is one of t

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9

Liang, Dong Cowles Mary Kathryn. "Issues in Bayesian Gaussian Markov random field models with application to intersensor calibration." Iowa City : University of Iowa, 2009. http://ir.uiowa.edu/etd/400.

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10

Liang, Dong. "Issues in Bayesian Gaussian Markov random field models with application to intersensor calibration." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/400.

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A long term record of the earth's vegetation is important in studies of global climate change. Over the last three decades, multiple data sets on vegetation have been collected using different satellite-based sensors. There is a need for methods that combine these data into a long term earth system data record. The Advanced Very High Resolution Radiometer (AVHRR) has provided reflectance measures of the entire earth since 1978. Physical and statistical models have been used to improve the consistency and reliability of this record. The Moderated Resolution Imaging Spectroradiometer (MODIS) has

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11

Ozturk, Mahir. "Markov Random Field Based Road Network Extraction From High Resoulution Satellite Images." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615499/index.pdf.

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Road Networks play an important role in various applications such as urban and rural planning, infrastructure planning, transportation management, vehicle navigation. Extraction of Roads from Remote Sensed satellite images for updating road database in geographical information systems (GIS) is generally done manually by a human operator. However, manual extraction of roads is time consuming and labor intensive process. In the existing literature, there are a great number of researches published for the purpose of automating the road extraction process. However, automated processes still yield

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12

Kim, Kyu-Heon. "Segmentation of natural texture images using a robust stochastic image model." Thesis, University of Newcastle Upon Tyne, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307927.

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13

Zhuang, Lili. "Bayesian Dynamical Modeling of Count Data." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1315949027.

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14

Wang, Chaohui. "Distributed and Higher-Order Graphical Models : towards Segmentation, Tracking, Matching and 3D Model Inference." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00658765.

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This thesis is devoted to the development of graph-based methods that address several of the most fundamental computer vision problems, such as segmentation, tracking, shape matching and 3D model inference. The first contribution of this thesis is a unified, single-shot optimization framework for simultaneous segmentation, depth ordering and multi-object tracking from monocular video sequences using a pairwise Markov Random Field (MRF). This is achieved through a novel 2.5D layered model where object-level and pixel-level representations are seamlessly combined through local constraints. Towar

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15

Luo, Simon Junming. "An Information Geometric Approach to Increase Representational Power in Unsupervised Learning." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25773.

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Machine learning models increase their representational power by increasing the number of parameters in the model. The number of parameters in the model can be increased by introducing hidden nodes, higher-order interaction effects or by introducing new features into the model. In this thesis we study different approaches to increase the representational power in unsupervised machine learning models. We investigate the use of incidence algebra and information geometry to develop novel machine learning models to include higher-order interactions effects into the model. Incidence algebra provide

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16

Kato, Jien, Toyohide Watanabe, Sébastien Joga, et al. "An HMM/MRF-based stochastic framework for robust vehicle tracking." IEEE, 2004. http://hdl.handle.net/2237/6743.

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17

Piao, Dongzhen. "Speeding Up Gibbs Sampling in Probabilistic Optical Flow." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/481.

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In today’s machine learning research, probabilistic graphical models are used extensively to model complicated systems with uncertainty, to help understanding of the problems, and to help inference and predict unknown events. For inference tasks, exact inference methods such as junction tree algorithms exist, but they suffer from exponential growth of cluster size and thus is not able to handle large and highly connected graphs. Approximate inference methods do not try to find exact probabilities, but rather give results that improve as algorithm runs. Gibbs sampling, as one of the approximate

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18

Lin, Shu-Chuan. "Robust estimation for spatial models and the skill test for disease diagnosis." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26681.

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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Lu, Jye-Chyi; Committee Co-Chair: Kvam, Paul; Committee Member: Mei, Yajun; Committee Member: Serban, Nicoleta; Committee Member: Vidakovic, Brani. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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19

Woodford, Oliver J. "Priors for new view synthesis." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:38962bda-6f0f-4158-89cf-8c641ebac486.

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New view synthesis (NVS) is the problem of generating a novel image of a scene, given a set of calibrated input images of the scene, i.e. their viewpoints, and also that of the output image, are known. The problem is generally ill-posed---a large number of scenes can generate a given set of images, therefore there may be many equally likely (given the input data) output views. Some of these views will look less natural to a human observer than others, so prior knowledge of natural scenes is required to ensure that the result is visually plausible. The aim of this thesis is to compare and impro

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20

Nallaivarothayan, Hajananth. "Video based detection of normal and anomalous behaviour of individuals." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/106947/1/Hajananth_Nallaivarothayan_Thesis.pdf.

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This PhD research has proposed novel computer vision and machine learning algorithms for the problem of video based anomalous event detection of individuals. Varieties of Hidden Markov Models were designed to model the temporal and spatial causalities of crowd behaviour. A Markov Random Field on top of a Gaussian Mixture Model is proposed to incorporate spatial context information during classification. Discriminative conditional random field methods are also proposed. Novel features are proposed to extract motion and appearance information. Most of the proposed approaches comprehensively outp

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21

Hua, Xiaoben, and Yuxia Yang. "A Fusion Model For Enhancement of Range Images." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2203.

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In this thesis, we would like to present a new way to enhance the “depth map” image which is called as the fusion of depth images. The goal of our thesis is to try to enhance the “depth images” through a fusion of different classification methods. For that, we will use three similar but different methodologies, the Graph-Cut, Super-Pixel and Principal Component Analysis algorithms to solve the enhancement and output of our result. After that, we will compare the effect of the enhancement of our result with the original depth images. This result indicates the effectiveness of our methodology.<b

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22

Wang, Chao. "Exploiting non-redundant local patterns and probabilistic models for analyzing structured and semi-structured data." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1199284713.

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23

Jiang, Huijing. "Statistical computation and inference for functional data analysis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37087.

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My doctoral research dissertation focuses on two aspects of functional data analysis (FDA): FDA under spatial interdependence and FDA for multi-level data. The first part of my thesis focuses on developing modeling and inference procedure for functional data under spatial dependence. The methodology introduced in this part is motivated by a research study on inequities in accessibility to financial services. The first research problem in this part is concerned with a novel model-based method for clustering random time functions which are spatially interdependent. A cluster consists of time

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24

Galvanin, Edinéia Aparecida dos Santos [UNESP]. "Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov." Universidade Estadual Paulista (UNESP), 2007. http://hdl.handle.net/11449/100258.

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Made available in DSpace on 2014-06-11T19:30:31Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-03-29Bitstream added on 2014-06-13T18:40:49Z : No. of bitstreams: 1 galvanin_eas_dr_prud.pdf: 5173646 bytes, checksum: aae51c2e230277eff607da015efe8a65 (MD5)<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)<br>As metodologias para a extração automática de telhados desempenham um papel importante no contexto de aquisição de informação espacial para Sistemas de Informação Geográficas (SIG). Neste sentido, este trabalho propõe uma metodologia para extração automática de c

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25

Moores, Matthew T. "Bayesian computational methods for spatial analysis of images." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/84728/12/84728%28thesis%29.pdf.

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This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

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26

Alvarado, Barrantes Ricardo. "Statistical models in biogeography." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3423067.

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We concentrate on the statistical methods used in Biogeography for modelling the spatial distribution of bird species. Due to the difficulty of specifying a joint multivariate spatial covariance structure in environmental processes, we factor such a joint distribution into a series of conditional models linked together in a hierarchical framework. We have a process that corresponds to an unobservable map with the actual information about a bird species, and the data correspond to the observations that are connected to that process. Markov chain Monte Carlo (MCMC) simulation approaches are used

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27

McGrath, Michael. "Markov random field image modelling." Master's thesis, University of Cape Town, 2003. http://hdl.handle.net/11427/5166.

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Includes bibliographical references.<br>This work investigated some of the consequences of using a priori information in image processing using computer tomography (CT) as an example. Prior information is information about the solution that is known apart from measurement data. This information can be represented as a probability distribution. In order to define a probability density distribution in high dimensional problems like those found in image processing it becomes necessary to adopt some form of parametric model for the distribution. Markov random fields (MRFs) provide just such a vehi

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28

Ferrante, Enzo. "Recalage déformable à base de graphes : mise en correspondance coupe-vers-volume et méthodes contextuelles." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC039/document.

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Les méthodes de recalage d’images, qui ont pour but l’alignement de deux ou plusieurs images dans un même système de coordonnées, sont parmi les algorithmes les plus anciens et les plus utilisés en vision par ordinateur. Les méthodes de recalage servent à établir des correspondances entre des images (prises à des moments différents, par différents senseurs ou avec différentes perspectives), lesquelles ne sont pas évidentes pour l’œil humain. Un type particulier d’algorithme de recalage, connu comme « les méthodes de recalage déformables à l’aide de modèles graphiques » est devenu de plus en pl

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29

Loubaton, Philippe. "Prediction et representation markovienne des processus stationnaires vectoriels sur z::(2) : utilisation de techniques d'estimation spectrale 2-d en traitement d'antenne." Paris, ENST, 1988. http://www.theses.fr/1988ENST0012.

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30

McGarry, Gregory John. "Model-based mammographic image analysis." Thesis, Queensland University of Technology, 2002.

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31

Sneltvedt, Tommy. "Sequential value information for Markov random field." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for fysikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13500.

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32

Forbes, Florence. "Modèles markoviens de ressources partagées." Phd thesis, Université Joseph Fourier (Grenoble), 1996. http://tel.archives-ouvertes.fr/tel-00004991.

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Selon les domaines d'applications, différentes façons de modéliser le partage de ressources ont été envisagées. Un des premiers modèles apparus est issu du "Dining Philosophers Problem" de Dijkstra, généralisé par la suite par Chandy et Misra à travers le "Drinking Philosophers Problem". Nous nous intéressons à des versions markoviennes de ces situations, dans lesquelles les durées pour la prise et l'utilisation des ressources sont aléatoires. L'évaluation puis l'optimisation des performances des systèmes de ressources partagées nous conduit à étudier l'équilibre de ces modèles. Cette étude s'

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33

Li, Min. "Markov Random field edge-centric image/video processing." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3274746.

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Thesis (Ph. D.)--University of California, San Diego, 2007.<br>Title from first page of PDF file (viewed October 8, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 117-125).

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34

Stoehr, Julien. "Méthodes d'inférence statistique pour champs de Gibbs." Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS132/document.

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La constante de normalisation des champs de Markov se présente sous la forme d'une intégrale hautement multidimensionnelle et ne peut être calculée par des méthodes analytiques ou numériques standard. Cela constitue une difficulté majeure pour l'estimation des paramètres ou la sélection de modèle. Pour approcher la loi a posteriori des paramètres lorsque le champ de Markov est observé, nous remplaçons la vraisemblance par une vraisemblance composite, c'est à dire un produit de lois marginales ou conditionnelles du modèle, peu coûteuses à calculer. Nous proposons une correction de la vraisembla

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35

Mannan, Fahim. "Markov random field based methods for cluttered scene stereo." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=95177.

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This thesis studies the performance of different Markov Random Field (MRF) based stereo formulations for cluttered scenes. Cluttered scenes have objects of a specific size distribution placed randomly in 3D space. Real-world examples of such scenes include forest canopy, bushes or foliages in general. One characteristic of such scenes is that they contain a lot of depth discontinuities and partially visible pixels. A natural question which is addressed in this thesis is how well the existing stereo algorithms perform for such scenes. The scenes used in some of the widely used benchmark dataset

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36

Korn, Christopher A. "Markov random field textures and applications in image processing." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/26619.

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In the field of image compression, transmission and reproduction, the foremost objective is to reduce the amount of information which must be transmitted. Currently the methods used to limit the amount of data which must be transmitted are compression algorithms using either lossless or lossy compression. Both of these methods start with the entire initial image and compress it using different techniques. This paper will address the use of Markov Random Field Textures in image processing. If there is a texture region in the initial image, the concept is to identify that region and match it to

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37

Milun, Davin. "Generating Markov random field image analysis systems from examples." Buffalo, N.Y. : Dept. of Computer Science, State University of New York at Buffalo, 1995. http://www.cse.buffalo.edu/tech%2Dreports/95%2D23.ps.Z.

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38

Larsen, Elisabeth Finserås. "Markov Random Field Modelling of Diagenetic Facies in Carbonate Reservoirs." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for matematiske fag, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11244.

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Bayesian inversion is performed on real observations to predict the diagenetic classes of a carbonate reservoir where the proportions of carbonate rock and depositional properties are known. The complete solution is the posterior model. The model is first developed in a 1D setting where the likelihood model is generalized Dirichlet distributed and the prior model is a Markov chain. The 1D model is used to justify the general assumptions on which the model is based. Thereafter the model is expanded to a 3D setting where the likelihood model remains the same and the prior model is a profile Mark

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39

Dai, Zhenwen, and 戴振文. "A Markov random field approach for multi-view normal integration." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B4308588X.

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Dai, Zhenwen. "A Markov random field approach for multi-view normal integration." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B4308588X.

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Falk, Matthew Gregory. "Incorporating uncertainty in environmental models informed by imagery." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/33235/1/Matthew_Falk_Thesis.pdf.

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In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given th

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Altay, Suhan. "On Forward Interest Rate Models: Via Random Fields And Markov Jump Processes." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608342/index.pdf.

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The essence of the interest rate modeling by using Heath-Jarrow-Morton framework is to find the drift condition of the instantaneous forward rate dynamics so that the entire term structure is arbitrage free. In this study, instantaneous forward interest rates are modeled using random fields and Markov Jump processes and the drift conditions of the forward rate dynamics are given. Moreover, the methodology presented in this study is extended to certain financial settings and instruments such as multi-country interest rate models, term structure of defaultable bond prices and forward measures. A

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43

Finch, Sam. "The random cluster model on the tree : Markov chains, random connections and boundary conditions." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/47385/.

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The Fortuin-Kasteleyn random cluster model was adapted to the tree by Häggström [38] who considered a Gibbs specification corresponding to "wired boundary conditions" on the tree. Grimmett and Janson [36] generalized this idea by considering boundary conditions defined by equivalence relations on the set of rays of the tree. In this thesis we continue this project by defining a new object, a "random connection;" a type of random equivalence relation that allows us to redefine what is meant by a cluster of edges on the tree. Our definition is general enough to include Grimmett and Janson's bo

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Minin, Volodymyr. "Exploring evolutionary heterogeneity with change-point models, Gaussian Markov random fields, and Markov chain induced counting processes." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1320942721&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Dai, Luyan. "Topics in objective bayesian methodology and spatio-temporal models." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/6084.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 4, 2009) Vita. Includes bibliographical references.

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Chen, Guo-Huei. "Image segmentation using a multiresolution random field model." Thesis, University of Warwick, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269395.

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Tang, Kam-Lun. "A Markov random field formulation for dense photometric stereo : theory, practice and applications /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?COMP%202005%20TANG.

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48

Merouani, Hayet Farida. "A Markov Random Field approach to the analysis of texture in digitised mammograms." Thesis, Robert Gordon University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302581.

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Häselich, Marcel [Verfasser]. "Markov random field terrain classification for autonomous robots in unstructured terrain / Marcel Häselich." Koblenz : Universitätsbibliothek Koblenz, 2015. http://d-nb.info/1064986544/34.

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Chaabene, Walid. "Scalable Structure Learning of Graphical Models." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/86263.

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Hypothesis-free learning is increasingly popular given the large amounts of data becoming available. Structure learning, a hypothesis-free approach, of graphical models is a field of growing interest due to the power of such models and lack of domain knowledge when applied on complex real-world data. State-of-the-art techniques improve on scalability of structure learning, which is often characterized by a large problem space. Nonetheless, these techniques still suffer computational bottlenecks that are yet to be approached. In this work, we focus on two popular models: dynamical linear syste

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