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Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty Quantification, and Insights Towards Safety 1st ed. 2022 edition
Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty Quantification, and Insights Towards Safety
This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence. Environment perception for highly automated driving heavily employs deep neural networks, facing many challenges.
427 pages, 103 Illustrations, color; 14 Illustrations, black and white; XVIII, 427 p. 117 illus., 10
| Media | Boeken Hardcover Book (Boek met harde rug en kaft) |
| Vrijgegeven | 18 juni 2022 |
| ISBN13 | 9783031012327 |
| Uitgevers | Springer International Publishing AG |
| Pagina's | 427 |
| Afmetingen | 243 × 165 × 30 mm · 812 g |
| Taal en grammatica | Duits |
| Uitgever | Fingscheidt, Tim |
| Uitgever | Gottschalk, Hanno |
| Uitgever | Houben, Sebastian |
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