41 citations
- Mercedes-Benz (Germany)DE5 papers
- University of OxfordGB5 papers
- California Institute of TechnologyUS3 papers
- University of ManchesterGB3 papers
- Baden-Wuerttemberg Cooperative State UniversityDE2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
- Rhodes UniversityZA2 papers
- TH Bingen University of Applied SciencesDE2 papers
- University of FreiburgDE2 papers
- University of StuttgartDE2 papers
- Arizona State UniversityUS1 paper
- Brandenburg University of Technology Cottbus-SenftenbergDE1 paper
22 papers
Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection
Kadir-Kaan Özer, René Ebeling, Markus Enzweiler
Multivariate time series anomalies often manifest as shifts in cross-channel dependencies rather than simple amplitude excursions. In autonomous driving, for instance, a steering c…
Assessing the Real-World Impact of Post-Quantum Cryptography on WPA-Enterprise Networks
Lukas Köder, Nils Lohmiller, Phil Schmieder +3
The advent of large-scale quantum computers poses a significant threat to contemporary network security protocols, including Wi-Fi Protected Access (WPA)-Enterprise authentication.…
STREAM-VAE: Dual-Path Routing for Slow and Fast Dynamics in Vehicle Telemetry Anomaly Detection
Kadir-Kaan Özer, René Ebeling, Markus Enzweiler
Automotive telemetry data exhibits slow drifts and fast spikes, often within the same sequence, making reliable anomaly detection challenging. Standard reconstruction-based methods…
Neural Rendering for Sensor Adaptation in 3D Object Detection
Felix Embacher, David Holtz, Jonas Uhrig +2
Autonomous vehicles often have varying camera sensor setups, which is inevitable due to restricted placement options for different vehicle types. Training a perception model on one…
Optimization-Based Comparative System Evaluation of Single and Dual Traction Inverters with Focus on Partial Load Efficiency and Chip Area
Christoph Sachs, Fabian Stamer, Jan Allgeier +2
The transition to electric transportation demands efficient and cost-effective powertrains. Optimizing energy use is crucial for extending range and reducing expenses. However, com…
Tiny Neural Networks for Multi-Object Tracking in a Modular Kalman Framework
Christian Alexander Holz, Christian Bader, Markus Enzweiler +1
We present a modular, production-ready approach that integrates compact Neural Network (NN) into a Kalmanfilter-based Multi-Object Tracking (MOT) pipeline. We design three tiny tas…