3 papers
cs.RO2026
Adaptive Learned State Estimation based on KalmanNet
Arian Mehrfard, Bharanidhar Duraisamy, Stefan Haag +2
Hybrid state estimators that combine model-based Kalman filtering with learned components have shown promise on simulated data, yet their performance on real-world automotive data…
cs.CV2025
Offline Auto Labeling: BAAS
Stefan Haag, Bharanidhar Duraisamy, Felix Govaers +3
This paper introduces BAAS, a new Extended Object Tracking (EOT) and fusion-based label annotation framework for radar detections in autonomous driving. Our framework utilizes Baye…
cs.RO2024
Performance Evaluation of Deep Learning-Based State Estimation: A Comparative Study of KalmanNet
Arian Mehrfard, Bharanidhar Duraisamy, Stefan Haag +1
Kalman Filters (KF) are fundamental to real-time state estimation applications, including radar-based tracking systems used in modern driver assistance and safety technologies. In…