146,87 €
163,19 €
-10% with code: EXTRA
Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
146,87
163,19 €
  • We will send in 10–14 business days.
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.
  • Publisher:
  • ISBN-10: 3658290161
  • ISBN-13: 9783658290160
  • Format: 14.8 x 21 x 1 cm, softcover
  • Language: English
  • SAVE -10% with code: EXTRA

Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces (e-book) (used book) | bookbook.eu

Reviews

(4.00 Goodreads rating)

Description

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.

EXTRA 10 % discount with code: EXTRA

146,87
163,19 €
We will send in 10–14 business days.

The promotion ends in 20d.15:32:47

The discount code is valid when purchasing from 10 €. Discounts do not stack.

Log in and for this item
you will receive 1,63 Book Euros!?
  • Author: Pascal Laube
  • Publisher:
  • ISBN-10: 3658290161
  • ISBN-13: 9783658290160
  • Format: 14.8 x 21 x 1 cm, softcover
  • Language: English English

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.

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)