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Publicado por World Scientific Publishing Co Pte Ltd, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Publicado por World Scientific Publishing Co Pte Ltd, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Publicado por World Scientific Publishing Co Pte Ltd, Singapore, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardcover. Condición: new. Hardcover. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Publicado por World Scientific Pub Co Inc, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardback. Condición: New. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.
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ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardback. Condición: New. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.
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Publicado por World Scientific Publishing Co Pte Ltd, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Publicado por World Scientific Pub Co Inc, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardcover. Condición: Brand New. 140 pages. 9.25x6.25x0.75 inches. In Stock.
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Publicado por World Scientific Publishing Co Pte Ltd, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoGebunden. Condición: New. KlappentextrnrnThis comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), .
Idioma: Inglés
Publicado por World Scientific Publishing Co Pte Ltd, SG, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardback. Condición: New. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.
Idioma: Inglés
Publicado por World Scientific Publishing Co Pte Ltd, Singapore, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
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Añadir al carritoHardcover. Condición: new. Hardcover. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Inglés
Publicado por World Scientific Publishing Co Pte Ltd, SG, 2022
ISBN 10: 9811253838 ISBN 13: 9789811253836
Librería: Rarewaves.com UK, London, Reino Unido
EUR 98,80
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Añadir al carritoHardback. Condición: New. This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.
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Añadir al carritoBuch. Condición: Neu. COMPUTATION GEOMETRY WITH INDEPENDENT & DEPENDENT UNCERTAIN | Gitik Rivka | Buch | Gebunden | Englisch | 2022 | World Scientific | EAN 9789811253836 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 90,65
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This comprehensive compendium describes a parametric model and algorithmic theory to represent geometric entities with dependent uncertainties between them. The theory, named Linear Parametric Geometric Uncertainty Model (LPGUM), is an expressive and computationally efficient framework that allows to systematically study geometric uncertainty and its related algorithms in computer geometry.The self-contained monograph is of great scientific, technical, and economic importance as geometric uncertainty is ubiquitous in mechanical CAD/CAM, robotics, computer vision, wireless networks and many other fields. Geometric models, in contrast, are usually exact and do not account for these inaccuracies.This useful reference text benefits academics, researchers, and practitioners in computer science, robotics, mechanical engineering and related fields.