8 citations · 8 across the 5 of their papers we have counts for
7 papers
Surgical Mask Detection with Convolutional Neural Networks and Data Augmentations on Spectrograms
Steffen Illium, Robert Müller, Andreas Sedlmeier +1
In many fields of research, labeled datasets are hard to acquire. This is where data augmentation promises to overcome the lack of training data in the context of neural network en…
Policy Entropy for Out-of-Distribution Classification
Andreas Sedlmeier, Robert Müller, Steffen Illium +1
One critical prerequisite for the deployment of reinforcement learning systems in the real world is the ability to reliably detect situations on which the agent was not trained. Su…
Trajectory annotation using sequences of spatial perception
Sebastian Feld, Steffen Illium, Andreas Sedlmeier +1
In the near future, more and more machines will perform tasks in the vicinity of human spaces or support them directly in their spatially bound activities. In order to simplify the…
Bayesian Surprise in Indoor Environments
Sebastian Feld, Andreas Sedlmeier, Markus Friedrich +2
This paper proposes a novel method to identify unexpected structures in 2D floor plans using the concept of Bayesian Surprise. Taking into account that a person's expectation is an…
Uncertainty-Based Out-of-Distribution Classification in Deep Reinforcement Learning
Andreas Sedlmeier, Thomas Gabor, Thomy Phan +2
Robustness to out-of-distribution (OOD) data is an important goal in building reliable machine learning systems. Especially in autonomous systems, wrong predictions for OOD inputs…
Adapting Quality Assurance to Adaptive Systems: The Scenario Coevolution Paradigm
Thomas Gabor, Marie Kiermeier, Andreas Sedlmeier +5
From formal and practical analysis, we identify new challenges that self-adaptive systems pose to the process of quality assurance. When tackling these, the effort spent on various…