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001 978-3-658-29017-7
003 DE-He213
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007 cr nn 008mamaa
008 200102s2020 gw | s |||| 0|eng d
020 _a9783658290177
_9978-3-658-29017-7
024 7 _a10.1007/978-3-658-29017-7
_2doi
050 4 _aQ325.5-.7
072 7 _aUYQM
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aUYQM
_2thema
082 0 4 _a006.31
_223
100 1 _aLaube, Pascal.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aMachine Learning Methods for Reverse Engineering of Defective Structured Surfaces
_h[electronic resource] /
_cby Pascal Laube.
250 _a1st ed. 2020.
264 1 _aWiesbaden :
_bSpringer Fachmedien Wiesbaden :
_bImprint: Springer Vieweg,
_c2020.
300 _aXV, 161 p. 56 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSchriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS),
_x2661-8095
505 0 _aMachine 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.
520 _aPascal 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. Contents 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 Target Groups Lecturers and students in the field of machine learning, geometric modeling and information theory Practitioners in the field of machine learning, surface reconstruction and CAD The Author 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.
650 0 _aMachine learning.
650 0 _aComputer-aided engineering.
650 0 _aManufactures.
650 1 4 _aMachine Learning.
650 2 4 _aComputer-Aided Engineering (CAD, CAE) and Design.
650 2 4 _aMachines, Tools, Processes.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783658290160
776 0 8 _iPrinted edition:
_z9783658290184
830 0 _aSchriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS),
_x2661-8095
856 4 0 _uhttps://doi.org/10.1007/978-3-658-29017-7
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c174078
_d174078