Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces

Pascal Laube

ISBN 10: 3658290161 / ISBN 13: 9783658290160

Published by Springer Fachmedien Wiesbaden Jan 2020, 2020

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 180 pp. Englisch.

Seller Inventory # 9783658290160

Bibliographic Details

• Title: Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
• Publisher: Springer Fachmedien Wiesbaden Jan 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 3658290161
• ISBN 13: 9783658290160
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 11D millimeters 210 millimeters width by 148 millimeters height by 11 millimeters depth
• Weight: 241 grams

About this title

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 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.