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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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Detalles Bibliográficos
Otros Autores: Fingscheidt, Tim (Editor), Gottschalk, Hanno (Editor), Houben, Sebastian (Editor)
Formato: Electrónico Capítulo de libro
Lenguaje:inglés
Publicado: Cham Springer Nature 2022
Materias:
Automotive technology & trades
Mathematical modelling
Image processing
Databases
Highly Automated Driving
Autonomous Driving
Environment Perception
Deep Learning
Safety
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