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Tapa Blanda. Zustand: Bien. Colección 'Computer Science Workbench'. Tapa Blanda. Profusamente ilustrado.9784431703099. Springer. Japón. 2001. 24x16 centímetros. 323 páginas. Tapa blanda. Estado=Bien. Inglés.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 362 | Sprache: Englisch | Produktart: Bücher | This detailed book presents a comprehensive study on the use of Markov Random Fields for solving computer vision problems. Various vision models are presented, and this third edition includes the most recent advances with new and expanded sections.
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 362 | Sprache: Englisch | Produktart: Bücher | This detailed book presents a comprehensive study on the use of Markov Random Fields for solving computer vision problems. Various vision models are presented, and this third edition includes the most recent advances with new and expanded sections.
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 362 | Sprache: Englisch | Produktart: Bücher | This detailed book presents a comprehensive study on the use of Markov Random Fields for solving computer vision problems. Various vision models are presented, and this third edition includes the most recent advances with new and expanded sections.
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In den WarenkorbHardback. Zustand: New. Third Edition 2009. Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; 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.
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Zustand: New. pp. 384 3rd Edition.
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Taschenbuch. Zustand: Neu. Markov Random Field Modeling in Image Analysis | Stan Z Li | Taschenbuch | xxii | Englisch | 2010 | Springer London | EAN 9781849967679 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; 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.
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In den WarenkorbHardback. Zustand: New. Third Edition 2009. Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; 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.
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Buch. Zustand: Neu. Neuware - Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; 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.
Soft cover. Zustand: New. Language:Chinese.Author:LIU GUO YING DENG BIAN ZHU.Binding:Soft cover.Publisher:Science Press.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when used with optimization principles. This book presents a comprehensive study on the use of MRFs for solving computer vision problems. Various vision models are presented in a unified framework, including image restoration and reconstruction, edge and region segmentation, texture, stereo and motion, object matching and recognition, and pose estimation. This third edition includes the most recent advances and has new and expanded sections on topics such as: Bayesian Network; Discriminative Random Fields; Strong Random Fields; Spatial-Temporal Models; 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. 362 pp. Englisch.
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In den WarenkorbKartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive coverage over a broad range of Markov Random Field TheoryProvides the most recent advances in the fieldMarkov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpre.
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In den WarenkorbGebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Comprehensive coverage over a broad range of Markov Random Field TheoryProvides the most recent advances in the fieldMarkov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpre.
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In den WarenkorbZustand: New. Print on Demand pp. 384 111 Illus.
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Zustand: New. PRINT ON DEMAND pp. 384.