Titlebook: Markov Random Field Modeling in Image Analysis; Stan Z. Li Book 20012nd edition Springer Japan 2001 Excel.Markov Random Field.Markov model

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gent systems: agents and data mining. LNAI, vol 4476. Springer, 2007), which synergizes the ubiquitous intelligence for handling complex intelligent problems and systems through the combined strengths of data mining, machine learning, and multiagent systems. Other typical examples that involve ubiqu

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Book 20012nd editiontterns (e.g. the FRAME model), Markov chain Monte Carlo (MCMC) methods, reversible jump MCMC. 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