• Title: Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty Quantification, and Insights Towards Safety
• Author(s) Tim Fingscheidt, Hanno Gottschalk, Sebastian Houben
• Publisher: Springer; 1st ed. 2022 edition (June 18, 2022); eBook (Creative Commons Licensed)
• License(s): Creative Commons License (CC)
• Hardcover: 445 pages
• eBook: PDF and ePub
• Language: English
• ISBN-10: 3031012321
• ISBN-13: 978-3031012327
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Book Description

This open access book brings together the latest developments from industry and research on automated driving and artificial intelligence.

It unites the views from both academia and industry, where computer vision and machine learning meet environment perception for highly automated driving.

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• Neural Networks and Deep Learning
• Robotics and Robot Programming
• Machine Learning
• Artificial Intelligence

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