Deep Neural Networks and Data for Automated Driving Robustness, Uncertainty Quantification, and Insights Towards Safety /

Deep Neural Networks and Data for Automated Driving Robustness, Uncertainty Quantification, and Insights Towards Safety /

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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. How much data do we need for training and testi...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Fingscheidt, Tim (Editor), Gottschalk, Hanno (Editor), Houben, Sebastian (Editor)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2022.
Edition:1st ed. 2022.
Subjects:
Automotive engineering.
Neural networks (Computer science) .
Computer vision.
Engineering > Data processing.
Automotive Engineering.
Mathematical Models of Cognitive Processes and Neural Networks.
Computer Vision.
Data Engineering.
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