4 citations · 4 across the 6 of their papers we have counts for
7 papers
Learning-Based Error Detection System for Advanced Vehicle Instrument Cluster Rendering
Cornelius Bürkle, Fabian Oboril, Kay-Ulrich Scholl
The automotive industry is currently expanding digital display options with every new model that comes onto the market. This entails not just an expansion in dimensions, resolution…
Global Clipper: Enhancing Safety and Reliability of Transformer-based Object Detection Models
Qutub Syed Sha, Michael Paulitsch, Karthik Pattabiraman +6
As transformer-based object detection models progress, their impact in critical sectors like autonomous vehicles and aviation is expected to grow. Soft errors causing bit flips dur…
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection
Qutub Syed, Michael Paulitsch, Korbinian Hagn +5
We introduce Situation Monitor, a novel zero-shot Out-of-Distribution (OOD) detection approach for transformer-based object detection models to enhance reliability in safety-critic…
Safe Perception -- A Hierarchical Monitor Approach
Cornelius Buerkle, Fabian Oboril, Johannes Burr +1
Our transportation world is rapidly transforming induced by an ever increasing level of autonomy. However, to obtain license of fully automated vehicles for widespread public use,…
Fault-Tolerant Perception for Automated Driving A Lightweight Monitoring Approach
Cornelius Buerkle, Florian Geissler, Michael Paulitsch +1
While the most visible part of the safety verification process of automated vehicles concerns the planning and control system, it is often overlooked that safety of the latter cruc…
Robustness of Object Detectors in Degrading Weather Conditions
Muhammad Jehanzeb Mirza, Cornelius Buerkle, Julio Jarquin +4
State-of-the-art object detection systems for autonomous driving achieve promising results in clear weather conditions. However, such autonomous safety critical systems also need t…
Precise localization relative to 3D Automated Driving map using the Decentralized Kalman filter with Feedback
Koba Natroshvili, Kai Storr, Fabian Oboril +1
This paper represents the novel high precision localization approach for Automated Driving (AD) relative to 3D map. The AD maps are not necessarily flat. Hence, the problem of loca…