Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces (Record no. 174078)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03337nam a22005295i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-658-29017-7 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423125103.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200102s2020 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783658290177 |
| -- | 978-3-658-29017-7 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-658-29017-7 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q325.5-.7 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQM |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MAT029000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQM |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Laube, Pascal. |
| Relator term | author. |
| Relator code | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 245 10 - TITLE STATEMENT | |
| Title | Machine Learning Methods for Reverse Engineering of Defective Structured Surfaces |
| Medium | [electronic resource] / |
| Statement of responsibility, etc | by Pascal Laube. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2020. |
| 264 #1 - | |
| -- | Wiesbaden : |
| -- | Springer Fachmedien Wiesbaden : |
| -- | Imprint: Springer Vieweg, |
| -- | 2020. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XV, 161 p. 56 illus. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS), |
| International Standard Serial Number | 2661-8095 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 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. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. 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 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer-aided engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Manufactures. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine Learning. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer-Aided Engineering (CAD, CAE) and Design. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machines, Tools, Processes. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783658290160 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783658290184 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Schriftenreihe der Institute für Systemdynamik (ISD) und optische Systeme (IOS), |
| -- | 2661-8095 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-658-29017-7">https://doi.org/10.1007/978-3-658-29017-7</a> |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
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