Titlebook: Markov Random Field Modeling in Image Analysis; Stan Z. Li Book 2009Latest edition Springer-Verlag London 2009 Bayesian modeling.Bayesian

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2191-6586 istical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas..978-1-84996-767-9978-1-84800-279-1Series ISSN 2191-6586 Series E-ISSN 2191-6594

侵害

facetious

High-Level MRF Models,se computation, pose meaning the geometric transformation from one coordinate system to another. In visual matching, the transformation is from the scene (image) to the model object considered (or vice versa). In derived models, the transformation is from a set of object features to a set of image f

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詳細(xì)目錄

Book 2009Latest editions; Learning MRF for Classification. This book is an excellent reference for researchers working in computer vision, image processing, statistical pattern recognition and applications of MRFs. It is also suitable as a text for advanced courses in these areas..

使出神

,Minimization – Local Methods,ery difficult in vision problems due to the complexity caused by interactions between labels. Therefore, optimal solutions are usually computed by using some iterative search techniques. This chapter describes techniques for finding local minima and discusses related issues.