33 citations · 87 across the 6 of their papers we have counts for
7 papers
Hardware faults that matter: Understanding and Estimating the safety impact of hardware faults on object detection DNNs
Syed Qutub, Florian Geissler, Yang Peng +4
Object detection neural network models need to perform reliably in highly dynamic and safety-critical environments like automated driving or robotics. Therefore, it is paramount to…
Cooperative RADAR Sensors for the Digital Test Field A9 (KoRA9): Algorithmic Recap and Lessons Learned
Sören Kohnert, Julian Stähler, Reinhard Stolle +1
Infrastructure sensing systems in combination with Infrastructure-to-Vehicle communication can be used to enhance sensor data obtained from the perspective of a vehicle, only. This…
Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision
Florian Geissler, Syed Qutub, Sayanta Roychowdhury +6
Convolutional neural networks (CNNs) have become an established part of numerous safety-critical computer vision applications, including human robot interactions and automated driv…
A Plausibility-based Fault Detection Method for High-level Fusion Perception Systems
Florian Geissler, Alex Unnervik, Michael Paulitsch
Trustworthy environment perception is the fundamental basis for the safe deployment of automated agents such as self-driving vehicles or intelligent robots. The problem remains tha…
Optimized sensor placement for dependable roadside infrastructures
Florian Geissler, Ralf Graefe
We present a multi-stage optimization method for efficient sensor deployment in traffic surveillance scenarios. Based on a genetic optimization scheme, our algorithm places an opti…
Designing a Roadside Sensor Infrastructure to Support Automated Driving
Florian Geissler, Sören Kohnert, Reinhard Stolle
Automation of complex traffic scenarios is expected to rely on input from a roadside infrastructure to complement the vehicles' environment perception. We here explore design requi…