Introduction to Bayesian Image Analysis

Introduction to Bayesian Image Analysis
Author:
Publisher:
Total Pages: 16
Release: 1993
Genre:
ISBN:


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The basic concepts in the application of Bayesian methods to image analysis are introduced. The Bayesian approach has benefits in image analysis and interpretation because it permits the use of prior knowledge concerning the situation under study. The fundamental ideas are illustrated with a number of examples ranging from a problem in one and two dimensions to large problems in image reconstruction that make use of sophisticated prior information.


Introduction to Bayesian Image Analysis
Language: en
Pages: 16
Authors:
Categories:
Type: BOOK - Published: 1993 - Publisher:

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The basic concepts in the application of Bayesian methods to image analysis are introduced. The Bayesian approach has benefits in image analysis and interpretat
Bayes' Rule
Language: en
Pages: 170
Authors: James V. Stone
Categories: Mathematics
Type: BOOK - Published: 2013-06-01 - Publisher: Sebtel Press

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In this richly illustrated book, a range of accessible examples are used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. The
An Introduction to Bayesian Analysis
Language: en
Pages: 356
Authors: Jayanta K. Ghosh
Categories: Mathematics
Type: BOOK - Published: 2007-07-03 - Publisher: Springer Science & Business Media

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This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate
Bayesian Statistics the Fun Way
Language: en
Pages: 258
Authors: Will Kurt
Categories: Mathematics
Type: BOOK - Published: 2019-07-09 - Publisher: No Starch Press

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Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a
Image Analysis, Random Fields and Markov Chain Monte Carlo Methods
Language: en
Pages: 389
Authors: Gerhard Winkler
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

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"This book is concerned with a probabilistic approach for image analysis, mostly from the Bayesian point of view, and the important Markov chain Monte Carlo met