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survAIval: Survival Analysis with the Eyes of AI
In this study, we propose a novel approach to enrich the training data for automated driving by using a self-designed driving simulator and two human drivers to generate safety-critical corner cases in a short period of time, as already presented in~\cite{kowol22simulator}.
A-Eye: Driving with the Eyes of AI for Corner Case Generation
For the test rig, a real-time semantic segmentation network is trained and integrated into the driving simulation software CARLA in such a way that a human can drive on the network's prediction.
YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors
In this work, we present an uncertainty-based method for sensor fusion with camera and radar data.
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