Thomas Stadelmayer

According to our database, Thomas Stadelmayer authored at least 9 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Lightweight and Person-Independent Radar-Based Hand Gesture Recognition for Classification and Regression of Continuous Gestures.

Thomas Stadelmayer, Youcef Hassab, Lorenzo Servadei, Avik Santra, Robert Weigel, Fabian Lurz

IEEE Internet Things J., May, 2024

Preprocessing and Classification Techniques for FMCW Radar and Deep Learning Based Indoor Motion Classification.

Thomas Stadelmayer

PhD thesis, 2024

2023

Out-of-Distribution Detection for Radar-based Gesture Recognition Using Metric-Learning.

Thomas Stadelmayer, Lorenzo Servadei, Avik Santra, Robert Weigel, Fabian Lurz

Proceedings of the IEEE Radio and Wireless Symposium, 2023

MEET: A Monte Carlo Exploration-Exploitation Trade-Off for Buffer Sampling.

Julius Ott, Lorenzo Servadei, Jose A. Arjona-Medina, Enrico Rinaldi, Gianfranco Mauro, Daniela Sanchez Lopera, Michael Stephan, Thomas Stadelmayer, Avik Santra, Robert Wille

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking.

Julius Ott, Lorenzo Servadei, Gianfranco Mauro, Thomas Stadelmayer, Avik Santra, Robert Wille

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Label-Aware Ranked Loss for Robust People Counting Using Automotive In-Cabin Radar.

Lorenzo Servadei, Huawei Sun, Julius Ott, Michael Stephan, Souvik Hazra, Thomas Stadelmayer, Daniela Sanchez Lopera, Robert Wille, Avik Santra

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Improved Target Detection and Feature Extraction using a Complex-Valued Adaptive Sine Filter on Radar Time Domain Data.

Thomas Stadelmayer, Avik Santra, Markus Stadelmayer, Robert Weigel, Fabian Lurz

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Human Activity Classification Using mm-Wave FMCW Radar by Improved Representation Learning.

Thomas Stadelmayer, Markus Stadelmayer, Avik Santra, Robert Weigel, Fabian Lurz

Proceedings of the mmNets@MobiCom 2020: Proceedings of the 4th ACM Workshop on Millimeter-Wave Networks and Sensing Systems, 2020

Radar Image Reconstruction from Raw ADC Data using Parametric Variational Autoencoder with Domain Adaptation.

Michael Stephan, Thomas Stadelmayer, Avik Santra, Georg Fischer, Robert Weigel, Fabian Lurz

Proceedings of the 25th International Conference on Pattern Recognition, 2020