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

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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Statistical Optimization for Geometric Computation: Theory and Practice - Taschenbuch

ISBN: 9780486443089

ID: 578418713

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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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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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 - gebrauchtes Buch

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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Details zum Buch
Statistical Optimization for Geometric Computation: Theory and Practice
Autor:

Kanatani, Kenichi

Titel:

Statistical Optimization for Geometric Computation: Theory and Practice

ISBN-Nummer:

9780486443089

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.

Detailangaben zum Buch - Statistical Optimization for Geometric Computation: Theory and Practice


EAN (ISBN-13): 9780486443089
ISBN (ISBN-10): 0486443086
Taschenbuch
Erscheinungsjahr: 2005
Herausgeber: DOVER PUBN INC
509 Seiten
Gewicht: 0,544 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 29.01.2008 15:15:00
Buch zuletzt gefunden am 23.10.2016 16:59:12
ISBN/EAN: 9780486443089

ISBN - alternative Schreibweisen:
0-486-44308-6, 978-0-486-44308-9

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