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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. Les mer
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Paperback
Legg i
Paperback
Legg i
Vår pris: 928,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

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.

Fakta

Innholdsfortegnelse

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.

Om forfatteren

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.