000 | 03804nam a22005895i 4500 | ||
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001 | 978-3-031-47560-3 | ||
003 | DE-He213 | ||
005 | 20240730170858.0 | ||
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008 | 240103s2024 sz | s |||| 0|eng d | ||
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_a9783031475603 _9978-3-031-47560-3 |
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024 | 7 |
_a10.1007/978-3-031-47560-3 _2doi |
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050 | 4 | _aTA347.A78 | |
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_a006.3 _223 |
100 | 1 |
_aNassif, Jimmy. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _995923 |
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245 | 1 | 0 |
_aSynthetic Data _h[electronic resource] : _bRevolutionizing the Industrial Metaverse / _cby Jimmy Nassif, Joe Tekli, Marc Kamradt. |
250 | _a1st ed. 2024. | ||
264 | 1 |
_aCham : _bSpringer Nature Switzerland : _bImprint: Springer, _c2024. |
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300 |
_aXXIX, 166 p. 64 illus., 59 illus. in color. _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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505 | 0 | _aCh. 1. Welcome to the Age of Industrial Data -- Ch. 2. Industrial Evolution toward the Age of Imagination -- Ch. 3. Background and Technologies -- Ch. 4. How Visual Data is Revolutionizing the Industry World -- Ch. 5. Digital Images - the Bread and Butter of Computer Vision -- Ch. 6. Creating SORDI: the Largest Synthetic Dataset for Industries -- Ch. 7. Towards an Industrial Robot Gym -- Ch. 8. What is Next with SORDI. | |
520 | _aThe book concentrates on the impact of digitalization and digital transformation technologies on the Industry 4.0 and smart factories, how the factory of tomorrow can be designed, built, and run virtually as a digital twin likeness of its real-world counterpart, before the physical structure is actually erected. It highlights the main digitalization technologies that have stimulated the Industry 4.0, how these technologies work and integrate with each other, and how they are shaping the industry of the future. It examines how multimedia data and digital images in particular are being leveraged to create fully virtualized worlds in the form of digital twin factories and fully virtualized industrial assets. It uses BMW Group's latest SORDI dataset (Synthetic Object Recognition Dataset for Industry), i.e., the largest industrial images dataset to-date and its applications at BMW Group and Idealworks, as one of the main explanatory scenarios throughout the book. It discusses the need of synthetic data to train advanced deep learning computer vision models, and how such datasets will help create the "robot gym" of the future: training robots on synthetic images to prepare them to function in the real world. | ||
650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aInternet of things. _94027 |
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650 | 0 |
_aMultimedia systems. _911575 |
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650 | 0 |
_aBig data. _94174 |
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650 | 0 |
_aComputer networks . _931572 |
|
650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aInternet of Things. _94027 |
650 | 2 | 4 |
_aMultimedia Information Systems. _931575 |
650 | 2 | 4 |
_aBig Data. _94174 |
650 | 2 | 4 |
_aComputer Communication Networks. _995929 |
700 | 1 |
_aTekli, Joe. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _995931 |
|
700 | 1 |
_aKamradt, Marc. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _995933 |
|
710 | 2 |
_aSpringerLink (Online service) _995935 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031475597 |
776 | 0 | 8 |
_iPrinted edition: _z9783031475610 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-47560-3 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
942 | _cEBK | ||
999 |
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