Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) / Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
(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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Klappentext zu „Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) / Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces “
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.
Inhaltsverzeichnis zu „Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) / Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces “
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.
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, XV, 161 Seiten, Maße: 14,8 x 1 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3658290161
- ISBN-13: 9783658290160
Sprache:
Englisch
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