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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) - used book

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 - Paperback

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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Statistical Optimization for Geometric Computation: Theory and Practice - new book

ISBN: 9780486443089

ID: 978048644308

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 - Paperback

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 - used book

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 of the book
Statistical Optimization for Geometric Computation: Theory and Practice
Author:

Kanatani, Kenichi

Title:

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.

Details of the book - Statistical Optimization for Geometric Computation: Theory and Practice


EAN (ISBN-13): 9780486443089
ISBN (ISBN-10): 0486443086
Paperback
Publishing year: 2005
Publisher: DOVER PUBN INC
509 Pages
Weight: 0,544 kg
Language: eng/Englisch

Book in our database since 29.01.2008 15:15:00
Book found last time on 23.10.2016 16:59:12
ISBN/EAN: 0486443086

ISBN - alternate spelling:
0-486-44308-6, 978-0-486-44308-9

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