机读格式显示(MARC)

• 000 01554cam a2200313 i 4500

• 001 0000837474

• 003 OCoLC

• 005 20250908132400.0

• 008 200111s2020 gw a b 001 0 eng d

• 020 __ |a 9783658290160 |q paperback

• 020 __ |z 9783658290177 |q electronic bk.

• 035 __ |a (OCoLC)1135663949 |z (OCoLC)1135282342

• 040 __ |a EBLCP |b eng |e rda |c EBLCP |d GW5XE |d YDX

• 050 _4 |a TA168.5

• 082 04 |a 620/.0042 |2 23

• 090 __ |a TB21/X5

• 093 __ |a TB21 |2 5

• 100 1_ |a Laube, Pascal, |e author.

• 245 10 |a Machine learning methods for reverse engineering of defective structured surfaces / |c Pascal Laube.

• 260 __ |a Wiesbaden : |b Springer Vieweg, |c 2020.

• 300 __ |a xiii, 160 pages : |b illustrations ; |c 22 cm.

• 336 __ |a text |b txt |2 rdacontent

• 337 __ |a unmediated |b n |2 rdamedia

• 338 __ |a volume |b nc |2 rdacarrier

• 490 0_ |a Schriftenreihe der Institute f眉r Systemdynamik (ISD) und Optische Systeme (IOS)

• 504 __ |a Includes bibliographical references and index.

• 520 __ |a 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.

• 650 _0 |a Reverse engineering |x Data processing.

• 650 _0 |a Machine learning.