1 code implementation • 24 Oct 2022 • Julius Ott, Lorenzo Servadei, Jose Arjona-Medina, Enrico Rinaldi, Gianfranco Mauro, Daniela Sánchez Lopera, Michael Stephan, Thomas Stadelmayer, Avik Santra, Robert Wille
This is enabled by the uncertainty estimation of the Q-Value function, which guides the sampling to explore more significant transitions and, thus, learn a more efficient policy.
no code implementations • 7 Oct 2022 • Huawei Sun, Lorenzo Servadei, Hao Feng, Michael Stephan, Robert Wille, Avik Santra
To address this, Explainable Artificial Intelligence (XAI) has been developing as a field that aims to improve the transparency of the model and increase their trustworthiness.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 30 May 2022 • Michael Stephan, Thomas Stadelmayer, Avik Santra, Georg Fischer, Robert Weigel, Fabian Lurz
This paper presents a parametric variational autoencoder-based human target detection and localization framework working directly with the raw analog-to-digital converter data from the frequency modulated continous wave radar.
no code implementations • 31 Mar 2022 • Souvik Hazra, Hao Feng, Gamze Naz Kiprit, Michael Stephan, Lorenzo Servadei, Robert Wille, Robert Weigel, Avik Santra
Gesture recognition is one of the most intuitive ways of interaction and has gathered particular attention for human computer interaction.
1 code implementation • 12 Oct 2021 • Lorenzo Servadei, Huawei Sun, Julius Ott, Michael Stephan, Souvik Hazra, Thomas Stadelmayer, Daniela Sanchez Lopera, Robert Wille, Avik Santra
In this paper, we introduce the Label-Aware Ranked loss, a novel metric loss function.