{"product_id":"9783658290160","title":"Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces (Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS)) (1st ed. 2020. 2020. xv, 161 S. 56 SW-Abb. 210 mm)","description":"\u003cp\u003ePascal 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. 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. 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.\u003c\/p\u003e","brand":"SPRINGER, BERLIN; SPRINGER FACHMEDIEN WIESBADEN; SPRI","offers":[{"title":"Default Title","offer_id":49202000953571,"sku":"00000_00000_00000_00000","price":69.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0764\/3758\/6147\/files\/9783658290160-1.jpg?v=1788434749","url":"https:\/\/usa.kinokuniya.com\/products\/9783658290160","provider":"Books Kinokuniya USA","version":"1.0","type":"link"}