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Record Nr. |
UNISA996472038103316 |
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Autore |
Benedek Csaba |
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Titolo |
Multi-level Bayesian models for environment perception / / Csaba Benedek |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2022] |
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©2022 |
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ISBN |
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9783030836542 |
9783030836535 |
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Descrizione fisica |
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1 online resource (208 pages) |
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Disciplina |
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Soggetti |
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Markov processes |
Bayesian statistical decision theory |
Reconeixement de formes (Informàtica) |
Visió per ordinador |
Models matemàtics |
Processos de Markov |
Estadística bayesiana |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Intro -- Acknowledgements -- Contents -- Acronyms and Notations -- Abbreviations and Concepts -- General Notations Used in the Book -- Specific Notations Used in MRF/CXM Models -- Specific Notations Used in MPP Models -- 1 Introduction -- 2 Fundamentals -- 2.1 Measurement Representation and Problem Formulations -- 2.2 Markovian Classification Models -- 2.2.1 Markov Random Fields, Gibbs Potentials, and Observation Processes -- 2.2.2 Bayesian Labeling Approach and the Potts Model -- 2.2.3 MRF-Based Image Segmentation -- 2.2.4 MRF Optimization -- 2.2.5 Mixed Markov Models -- 2.3 Object Population Extraction with Marked Point Processes -- 2.3.1 Definition of Marked Point Processes -- 2.3.2 MPP Energy Functions -- 2.3.3 MPP Optimization -- 2.4 Methodological Contributions of the Book -- 3 Bayesian Models for Dynamic Scene Analysis -- 3.1 Dynamic |
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