Investigation of Uncertainty of Deep Learning-based Object Classification on Radar Spectra

no code implementations • 1 Jun 2021 • Kanil Patel, William Beluch, Kilian Rambach, Adriana-Eliza Cozma, Michael Pfeiffer, Bin Yang

Deep learning (DL) has recently attracted increasing interest to improve object type classification for automotive radar. In addition to high accuracy, it is crucial for decision making in autonomous vehicles to evaluate the reliability of the predictions; however, decisions of DL networks are non-transparent.

Autonomous Vehicles Decision Making +3

DeepHybrid: Deep Learning on Automotive Radar Spectra and Reflections for Object Classification

no code implementations • 17 Feb 2022 • Adriana-Eliza Cozma, Lisa Morgan, Martin Stolz, David Stoeckel, Kilian Rambach

Automated vehicles need to detect and classify objects and traffic participants accurately.

Collision Avoidance Neural Architecture Search