Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces (Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS)) - Softcover

Laube, Pascal

Softcover

ISBN 10: 3658290161 ISBN 13: 9783658290160

Publisher: Springer Vieweg, 2020

Synopsis

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.

About this title

About 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.

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.

Edition details

• Publisher: Springer Vieweg
• Publication date: 2020
• Language: English
• ISBN 10: 3658290161
• ISBN 13: 9783658290160
• Binding: Paperback
• Edition number: 1
• Number of pages: 176