While automated driving is often advertised with better-than-human driving performance, this
chapter reviews that it is nearly impossible to provide direct statistical evidence on the …

With the growing use of Deep Neural Networks (DNNs) in various safety-critical applications
comes an increasing need for Verification and Validation (V&V) of these DNNs. Unlike …

When employing deep neural networks (DNNs) for semantic segmentation in safety-critical
applications like automotive perception or medical imaging, it is important to estimate their …

This work deals with the usability of synthetically generated data for training and validation
of visual perception functions applied in autonomous driving. Synthetically generated …

The rapid advancement of artificial intelligence (AI) systems in recent years is largely due to
the impressive capabilities of artificial neural networks. Their powerful capabilities in natural …