3 papers
cs.AI2025
Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization
Lucas Heublein, Tobias Feigl, Thorsten Nowak +3
Jamming devices disrupt signals from the global navigation satellite system (GNSS) and pose a significant threat, as they compromise the robustness of accurate positioning. The det…
cs.CV2025
Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning
Nisha L. Raichur, Lucas Heublein, Tobias Feigl +3
The primary objective of methods in continual learning is to learn tasks in a sequential manner over time (sometimes from a stream of data), while mitigating the detrimental phenom…
eess.SP2024
Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data
Felix Ott, Lucas Heublein, Nisha Lakshmana Raichur +4
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning. Detecting a…