000 | 03337nam a22005295i 4500 | ||
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001 | 978-3-658-29017-7 | ||
003 | DE-He213 | ||
005 | 20240423125103.0 | ||
007 | cr nn 008mamaa | ||
008 | 200102s2020 gw | s |||| 0|eng d | ||
020 |
_a9783658290177 _9978-3-658-29017-7 |
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024 | 7 |
_a10.1007/978-3-658-29017-7 _2doi |
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_aUYQM _2bicssc |
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_aMAT029000 _2bisacsh |
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_aUYQM _2thema |
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_a006.31 _223 |
100 | 1 |
_aLaube, Pascal. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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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. |
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300 |
_aXV, 161 p. 56 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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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 |