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Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces
Knygos.lt klubas Knygos.lt nariams
106,39 €
-30%
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151,99 €
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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.
  • Leidėjas:
  • ISBN-10: 3658290161
  • ISBN-13: 9783658290160
  • Formatas: 14.8 x 21 x 1 cm, minkšti viršeliai
  • Kalba: Anglų

Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces (el. knyga) (skaityta knyga) | knygos.lt

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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.

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  • Autorius: Pascal Laube
  • Leidėjas:
  • ISBN-10: 3658290161
  • ISBN-13: 9783658290160
  • Formatas: 14.8 x 21 x 1 cm, minkšti viršeliai
  • Kalba: Anglų

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.

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