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Statistical Optimization for Geometric Computation: Theory and Practice (Dover Books on Mathematics) - Kenichi Kanatani; Mathematics
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Kenichi Kanatani; Mathematics:

Statistical Optimization for Geometric Computation: Theory and Practice (Dover Books on Mathematics) - livre d'occasion

ISBN: 0486443086

ID: 6798445

This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and sensors.The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. The numerous mathematical prerequisites for developing the theories are explained systematically in separate chapters. These methods range from linear algebra, optimization, and geometry to a detailed statistical theory of geometric patterns, fitting estimates, and model selection. In addition, examples drawn from both synthetic and real data demonstrate the insufficiencies of conventional procedures and the improvements in accuracy that result from the use of optimal methods. algorithms,artificial intelligence,computer science,computers and technology,education and reference,machine vision,mathematics,pattern recognition,programming,robotics Computer Science, Dover Publications

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Statistical Optimization for Geometric Computation: Theory and Practice - Mathematics
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Mathematics:

Statistical Optimization for Geometric Computation: Theory and Practice - Livres de poche

ISBN: 9780486443089

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Dover Publications. Paperback. New. Paperback. 526 pages. Dimensions: 8.4in. x 5.4in. x 1.1in.This text for graduate students discusses the mathematical foundations of statistical inference for building three-dimensional models from image and sensor data that contain noise--a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. The numerous mathematical prerequisites for developing the theories are explained systematically in separate chapters. These methods range from linear algebra, optimization, and geometry to a detailed statistical theory of geometric patterns, fitting estimates, and model selection. In addition, examples drawn from both synthetic and real data demonstrate the insufficiencies of conventional procedures and the improvements in accuracy that result from the use of optimal methods. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN., Dover Publications

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Statistical Optimization for Geometric Computation: Theory and Practice - Kenichi Kanatani
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Statistical Optimization for Geometric Computation: Theory and Practice - nouveau livre

ISBN: 9780486443089

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This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise — a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition. Kenichi Kanatani, Books, Science and Nature, Statistical Optimization for Geometric Computation: Theory and Practice Books>Science and Nature, Dover Publications

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Statistical Optimization for Geometric Computation: Theory and Practice - Kanatani, Kenichi
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Kanatani, Kenichi:
Statistical Optimization for Geometric Computation: Theory and Practice - Livres de poche

ISBN: 9780486443089

[ED: Taschenbuch], [PU: DOVER PUBN INC], This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise -- a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition. Versandfertig in über 4 Wochen, [SC: 0.00], Neuware, gewerbliches Angebot

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Statistical Optimization for Geometric Computation: Theory and Practice - Kanatani, Kenichi
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Kanatani, Kenichi:
Statistical Optimization for Geometric Computation: Theory and Practice - livre d'occasion

1996, ISBN: 9780486443089

ID: 1603861

This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise -- a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition. Statistical Optimization for Geometric Computation: Theory and Practice Kanatani, Kenichi, Dover Publications

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Détails sur le livre
Statistical Optimization for Geometric Computation: Theory and Practice
Auteur:

Kanatani, Kenichi

Titre:

Statistical Optimization for Geometric Computation: Theory and Practice

ISBN:

0486443086

This text discusses the mathematical foundations of statistical inference for building 3-dimensional models from image and sensor data that contain noise -- a task involving autonomous robots guided by video cameras and sensors. The text employs a theoretical accuracy for the optimization procedure, which maximizes the reliability of estimations based on noise data. 1996 edition.

Informations détaillées sur le livre - Statistical Optimization for Geometric Computation: Theory and Practice


EAN (ISBN-13): 9780486443089
ISBN (ISBN-10): 0486443086
Livre de poche
Date de parution: 2005
Editeur: DOVER PUBN INC
509 Pages
Poids: 0,544 kg
Langue: eng/Englisch

Livre dans la base de données depuis 29.01.2008 15:15:00
Livre trouvé récemment le 23.10.2016 16:59:12
ISBN/EAN: 0486443086

ISBN - Autres types d'écriture:
0-486-44308-6, 978-0-486-44308-9

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