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

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Detalhes bibliográficos
Outros Autores:	Fingscheidt, Tim (Editor), Gottschalk, Hanno (Editor), Houben, Sebastian (Editor)
Formato:	Recurso Electrónico Capítulo de Livro
Idioma:	inglês
Publicado em:	Cham Springer Nature 2022
Assuntos:	Automotive technology & trades Mathematical modelling Image processing Databases Highly Automated Driving Autonomous Driving Environment Perception Deep Learning Safety
Acesso em linha:	OAPEN Library: download the publication OAPEN Library: description of the publication
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Deep Neural Networks and Data for Automated Driving Robustness, Uncertainty Quantification, and Insights Towards Safety

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