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Über die Autorin bzw. den Autor
Ulf Grenander is the L. Herbert Ballou University Professor at Brown University. He is a member of the Royal Swedish Academy of Science and an honorary fellow of the Royal Statistical Society in London
Michael Miller is the Professor of Electrical and Computer Engineering, Director of the Center for Imaging Science, and Professor of Biomedical Engineering at Johns Hopkins University, Baltimore. He completed his Ph.D. in Biomedical Engineering at The Johns Hopkins University in 1983.
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- VerlagAcademic
- Erscheinungsdatum2006
- ISBN 10 0198505701
- ISBN 13 9780198505709
- EinbandTapa dura
- SpracheEnglisch
- Anzahl der Seiten610
- Kontakt zum HerstellerNicht verfügbar
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Pattern Theory: From representation to inference (eng)
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Pattern Theory: From Representation to Inference
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Pattern Theory: From Representation to Inference
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Pattern Theory : From Representation to Inference
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Pattern Theory : From Representation to Inference
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Pattern Theory : From Representation to Inference
Verlag:
Oxford University Press, 2007
ISBN 10: 0198505701
ISBN 13: 9780198505709
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Pattern Theory (Hardcover)
Verlag:
Oxford University Press, Oxford, 2006
ISBN 10: 0198505701
ISBN 13: 9780198505709
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Hardcover. Zustand: new. Hardcover. Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website.The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes. Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computer science, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website. The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometric transformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum. Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look at inference, exploring random sampling approaches for estimation of model order and parametric representing of shapes. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9780198505709
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Pattern Theory : From Representation to Inference
Verlag:
Oxford University Press, 2007
ISBN 10: 0198505701
ISBN 13: 9780198505709
Gebraucht
Hardcover
Anbieter: GreatBookPrices, Columbia, MD, USA
Verkäuferbewertung 5 von 5 Sternen
Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 4252583
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Pattern Theory: From Representation to Inference
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Buch. Zustand: Neu. Neuware - Pattern Theory provides a comprehensive and accessible overview of the modern challenges in signal, data, and pattern analysis in speech recognition, computational linguistics, image analysis and computer vision. Aimed at graduate students in biomedical engineering, mathematics, computerscience, and electrical engineering with a good background in mathematics and probability, the text includes numerous exercises and an extensive bibliography. Additional resources including extended proofs, selected solutions and examples are available on a companion website.The book commences with a short overview of pattern theory and the basics of statistics and estimation theory. Chapters 3-6 discuss the role of representation of patterns via condition structure. Chapters 7 and 8 examine the second central component of pattern theory: groups of geometrictransformation applied to the representation of geometric objects. Chapter 9 moves into probabilistic structures in the continuum, studying random processes and random fields indexed over subsets of Rn. Chapters 10 and 11 continue with transformations and patterns indexed over the continuum.Chapters 12-14 extend from the pure representations of shapes to the Bayes estimation of shapes and their parametric representation. Chapters 15 and 16 study the estimation of infinite dimensional shape in the newly emergent field of Computational Anatomy. Finally, Chapters 17 and 18 look atinference, exploring random sampling approaches for estimation of model order and parametric representing of shapes. Bestandsnummer des Verkäufers 9780198505709
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