1 citations · 1 across the 2 of their papers we have counts for
3 papers
Deep Learning Safety Concerns in Automated Driving Perception
Stephanie Abrecht, Alexander Hirsch, Shervin Raafatnia +1
Recent advances in the field of deep learning and impressive performance of deep neural networks (DNNs) for perception have resulted in an increased demand for their use in automat…
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben, Stephanie Abrecht, Maram Akila +38
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These s…
Safety Concerns and Mitigation Approaches Regarding the Use of Deep Learning in Safety-Critical Perception Tasks
Oliver Willers, Sebastian Sudholt, Shervin Raafatnia +1
Deep learning methods are widely regarded as indispensable when it comes to designing perception pipelines for autonomous agents such as robots, drones or automated vehicles. The m…