| 書目名稱 | Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces |
| 編輯 | Pascal Laube |
| 視頻video | http://file.papertrans.cn/621/620407/620407.mp4 |
| 概述 | Demonstrates that machine learning can be a viable part of the CAD reverse engineering pipeline.Scientific-technical study |
| 叢書名稱 | Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS) |
| 圖書封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2020 |
| 關(guān)鍵詞 | Machine Learning Methods; CAD Reverse Engineering; Defective Structured Surfaces; Surface Reconstructio |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-658-29017-7 |
| isbn_softcover | 978-3-658-29016-0 |
| isbn_ebook | 978-3-658-29017-7Series ISSN 2661-8087 Series E-ISSN 2661-8095 |
| issn_series | 2661-8087 |
| copyright | Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020 |