Download or read book Stochastic Geometry Models in Image Analysis and Spatial Statistics written by M. N. M. Van Lieshout and published by . This book was released on 1991 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Geometry Spatial Statistics and Random Fields written by Volker Schmidt and published by Springer. This book was released on 2014-10-24 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.
Download or read book Stochastic Geometry for Image Analysis written by Xavier Descombes and published by John Wiley & Sons. This book was released on 2013-05-06 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
Download or read book Spatial Statistics and Digital Image Analysis written by National Research Council and published by National Academies Press. This book was released on 1991-02-01 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial statistics is one of the most rapidly growing areas of statistics, rife with fascinating research opportunities. Yet many statisticians are unaware of those opportunities, and most students in the United States are never exposed to any course work in spatial statistics. Written to be accessible to the nonspecialist, this volume surveys the applications of spatial statistics to a wide range of areas, including image analysis, geosciences, physical chemistry, and ecology. The book describes the contributions of the mathematical sciences, summarizes the current state of knowledge, and identifies directions for research.
Download or read book Stochastic Geometry written by Wilfrid S. Kendall and published by Routledge. This book was released on 2019-06-10 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including: o a "crash-course" introduction to key stochastic geometry themes o considerations of geometric sampling bias issues o tesselations o shape o random sets o image analysis o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo
Download or read book Case Studies in Spatial Point Process Modeling written by Adrian Baddeley and published by Springer Science & Business Media. This book was released on 2006-03-03 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. From the reviews: "For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006
Download or read book Stochastic Geometry written by David Coupier and published by Springer. This book was released on 2019-04-09 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume offers a unique and accessible overview of the most active fields in Stochastic Geometry, up to the frontiers of recent research. Since 2014, the yearly meeting of the French research structure GDR GeoSto has been preceded by two introductory courses. This book contains five of these introductory lectures. The first chapter is a historically motivated introduction to Stochastic Geometry which relates four classical problems (the Buffon needle problem, the Bertrand paradox, the Sylvester four-point problem and the bicycle wheel problem) to current topics. The remaining chapters give an application motivated introduction to contemporary Stochastic Geometry, each one devoted to a particular branch of the subject: understanding spatial point patterns through intensity and conditional intensities; stochastic methods for image analysis; random fields and scale invariance; and the theory of Gibbs point processes. Exposing readers to a rich theory, this book will encourage further exploration of the subject and its wide applications.
Download or read book Stochastic Geometry and Its Applications written by Dietrich Stoyan and published by Wiley-Blackwell. This book was released on 1995 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: The exposition is mathematically precise and takes into account the latest results. However, in many cases proofs are omitted. Applied scientists who may not wish to follow the mathematical arguments in detail will still be able to interpret and use the formulae.
Download or read book Stochastic Geometry written by Wilfrid S. Kendall and published by Routledge. This book was released on 2019-06-10 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry involves the study of random geometric structures, and blends geometric, probabilistic, and statistical methods to provide powerful techniques for modeling and analysis. Recent developments in computational statistical analysis, particularly Markov chain Monte Carlo, have enormously extended the range of feasible applications. Stochastic Geometry: Likelihood and Computation provides a coordinated collection of chapters on important aspects of the rapidly developing field of stochastic geometry, including: o a "crash-course" introduction to key stochastic geometry themes o considerations of geometric sampling bias issues o tesselations o shape o random sets o image analysis o spectacular advances in likelihood-based inference now available to stochastic geometry through the techniques of Markov chain Monte Carlo
Download or read book Statistical Analysis and Modelling of Spatial Point Patterns written by Dr. Janine Illian and published by John Wiley & Sons. This book was released on 2008-04-15 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space. Examples include locations of trees in a forest, blood particles on a glass plate, galaxies in the universe, and particle centres in samples of material. Numerous aspects of the nature of a specific spatial point pattern may be described using the appropriate statistical methods. Statistical Analysis and Modelling of Spatial Point Patterns provides a practical guide to the use of these specialised methods. The application-oriented approach helps demonstrate the benefits of this increasingly popular branch of statistics to a broad audience. The book: Provides an introduction to spatial point patterns for researchers across numerous areas of application Adopts an extremely accessible style, allowing the non-statistician complete understanding Describes the process of extracting knowledge from the data, emphasising the marked point process Demonstrates the analysis of complex datasets, using applied examples from areas including biology, forestry, and materials science Features a supplementary website containing example datasets. Statistical Analysis and Modelling of Spatial Point Patterns is ideally suited for researchers in the many areas of application, including environmental statistics, ecology, physics, materials science, geostatistics, and biology. It is also suitable for students of statistics, mathematics, computer science, biology and geoinformatics.
Download or read book Selected Proceedings of the Symposium on Inference for Stochastic Processes written by Ishwar V. Basawa and published by IMS. This book was released on 2001 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Modeling for Medical Image Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2015-11-18 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Modeling for Medical Image Analysis provides a brief introduction to medical imaging, stochastic modeling, and model-guided image analysis.Today, image-guided computer-assisted diagnostics (CAD) faces two basic challenging problems. The first is the computationally feasible and accurate modeling of images from different modalities to obt
Download or read book Spatial Cluster Modelling written by Andrew B. Lawson and published by CRC Press. This book was released on 2002-05-16 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this b
Download or read book Advances In Theory And Applications Of Random Sets Proceedings Of The Symposium written by Dominique Jeulin and published by World Scientific. This book was released on 1997-01-16 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers topics ranging from pure and applied mathematics to pedagogical issues in mathematics. There are papers in mathematical biology, differential equations, difference equations, dynamical systems, orthogonal polynomials, topology, calculus reform, algebra, and numerical analysis. Most of the papers include new, interesting results that are at the cutting edge of the respective subjects. However, there are some papers of an expository nature.
Download or read book Stochastic Analysis for Poisson Point Processes written by Giovanni Peccati and published by Springer. This book was released on 2016-07-07 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic geometry is the branch of mathematics that studies geometric structures associated with random configurations, such as random graphs, tilings and mosaics. Due to its close ties with stereology and spatial statistics, the results in this area are relevant for a large number of important applications, e.g. to the mathematical modeling and statistical analysis of telecommunication networks, geostatistics and image analysis. In recent years – due mainly to the impetus of the authors and their collaborators – a powerful connection has been established between stochastic geometry and the Malliavin calculus of variations, which is a collection of probabilistic techniques based on the properties of infinite-dimensional differential operators. This has led in particular to the discovery of a large number of new quantitative limit theorems for high-dimensional geometric objects. This unique book presents an organic collection of authoritative surveys written by the principal actors in this rapidly evolving field, offering a rigorous yet lively presentation of its many facets.
Download or read book Stochastic Geometry Spatial Statistics and Random Fields written by Evgeny Spodarev and published by Springer. This book was released on 2013-02-11 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a modern introduction to stochastic geometry, random fields and spatial statistics at a (post)graduate level. It is focused on asymptotic methods in geometric probability including weak and strong limit theorems for random spatial structures (point processes, sets, graphs, fields) with applications to statistics. Written as a contributed volume of lecture notes, it will be useful not only for students but also for lecturers and researchers interested in geometric probability and related subjects.
Download or read book Pattern Recognition From Classical To Modern Approaches written by Sankar Kumar Pal and published by World Scientific. This book was released on 2001-11-23 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource.
