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Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic
Therefore, this work presents a novel method for self-assessment of single-object tracking in clutter based on Kalman filtering and subjective logic.
Anomaly Detection in Radar Data Using PointNets
On the one hand, radar offers a direct measurement of the radial velocity of targets in the environment.
Kalman Filter Meets Subjective Logic: A Self-Assessing Kalman Filter Using Subjective Logic
Thus, by embedding classical Kalman filtering into subjective logic, our method additionally features an explicit measure for statistical uncertainty in the self-assessment.
2D Car Detection in Radar Data with PointNets
To this end, PointNets are adjusted for radar data performing 2D object classification with segmentation, and 2D bounding box regression in order to estimate an amodal 2D bounding box.
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