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cs.CV2023★ 2 cited
Deep Learning Method for Cell-Wise Object Tracking, Velocity Estimation and Projection of Sensor Data over Time
Marco Braun, Moritz Luszek, Mirko Meuter +3
Current Deep Learning methods for environment segmentation and velocity estimation rely on Convolutional Recurrent Neural Networks to exploit spatio-temporal relationships within o…
cs.LG2023★ 4 cited
Quantification of Uncertainties in Deep Learning-based Environment Perception
Marco Braun, Moritz Luszek, Jan Siegemund +2
In this work, we introduce a novel Deep Learning-based method to perceive the environment of a vehicle based on radar scans while accounting for uncertainties in its predictions. T…
cs.CV2023★ 3 cited
Semantic Segmentation of Radar Detections using Convolutions on Point Clouds
Marco Braun, Alessandro Cennamo, Markus Schoeler +2
For autonomous driving, radar sensors provide superior reliability regardless of weather conditions as well as a significantly high detection range. State-of-the-art algorithms for…