Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces / Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) (PDF)
(Sprache: Englisch)
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The...
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Produktinformationen zu „Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces / Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) (PDF)“
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Contents
- Machine Learning Methods for Parametrization in Curve and Surface Approximation
- Classification of Geometric Primitives in Point Clouds
- Image Inpainting for High-resolution Textures Using CNN Texture Synthesis
Target Groups
- Lecturers and students in the field of machine learning, geometric modeling and information theory
- Practitioners in the field of machine learning, surface reconstruction and CAD
The Author
Pascal Laube's main research interest is the development of machine learning methods for CAD reverse engineering. He is currently developing self-driving cars for an international operating German enterprise in the field of mobility, automotive and industrial technology.
Autoren-Porträt von Pascal Laube
Pascal Laube's main research interest is the development of machine learning methods for CAD reverse engineering. He is currently developing self-driving cars for an international operating German enterprise in the field of mobility, automotive and industrial technology.
Bibliographische Angaben
- Autor: Pascal Laube
- 2020, 1st ed. 2020, 161 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 365829017X
- ISBN-13: 9783658290177
- Erscheinungsdatum: 02.01.2020
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 7.36 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
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