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Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty Quantification, and Insights Towards Safety 1st ed. 2022 edition
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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
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2022. gada 18. jūnijs |
| ISBN13 | 9783031012327 |
| Izdevēji | Springer International Publishing AG |
| Lapas | 427 |
| Izmēri | 243 × 165 × 30 mm · 812 g |
| Valoda | Vācu |
| Redaktors | Fingscheidt, Tim |
| Redaktors | Gottschalk, Hanno |
| Redaktors | Houben, Sebastian |
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