12 papers
Comprehensive Robustness Analysis of LiDAR-based 3D Object Detection in Autonomous Driving
Adwait Chandorkar, Kai Krink, Yerdana Maulenbay +2
Recent advancements in LiDAR-only 3D object detection have demonstrated improved detection accuracy over benchmark datasets. However, the adversarial robustness of these models rem…
ConTex: Reformulating Counterfactual Generation For Time Series Forecasting
Jan Voets, Hasan Tercan, Tobias Meisen +1
Decision-making with deep learning-based time series forecasting requires not only accurate predictions but also actionable insights. However, current architectures do not inherent…
Out of Distribution Detection for Efficient Continual Learning in Quality Prediction for Arc Welding
Yannik Hahn, Jan Voets, Antonin Koenigsfeld +2
Modern manufacturing relies heavily on fusion welding processes, including gas metal arc welding (GMAW). Despite significant advances in machine learning-based quality prediction,…
EXCODER: EXplainable Classification Of DiscretE time series Representations
Yannik Hahn, Antonin Königsfeld, Hasan Tercan +1
Deep learning has significantly improved time series classification, yet the lack of explainability in these models remains a major challenge. While Explainable AI (XAI) techniques…
Graph Query Networks for Object Detection with Automotive Radar
Loveneet Saini, Hasan Tercan, Tobias Meisen
Object detection with 3D radar is essential for 360-degree automotive perception, but radar's long wavelengths produce sparse and irregular reflections that challenge traditional g…
Rethinking Backbone Design for Lightweight 3D Object Detection in LiDAR
Adwait Chandorkar, Hasan Tercan, Tobias Meisen
Recent advancements in LiDAR-based 3D object detection have significantly accelerated progress toward the realization of fully autonomous driving in real-world environments. Despit…