2 citations · 5 across the 3 of their papers we have counts for
6 papers
Addressing Data Scarcity in Multimodal User State Recognition by Combining Semi-Supervised and Supervised Learning
Hendric Voß, Heiko Wersing, Stefan Kopp
Detecting mental states of human users is crucial for the development of cooperative and intelligent robots, as it enables the robot to understand the user's intentions and desires…
Intuitiveness in Active Teaching
Jan Philip Göpfert, Ulrike Kuhl, Lukas Hindemith +2
While Machine learning gives rise to astonishing results in automated systems, it is usually at the cost of large data requirements. This makes many successful algorithms from mach…
Interpretable Locally Adaptive Nearest Neighbors
Jan Philip Göpfert, Heiko Wersing, Barbara Hammer
When training automated systems, it has been shown to be beneficial to adapt the representation of data by learning a problem-specific metric. This metric is global. We extend this…
Recovering Localized Adversarial Attacks
Jan Philip Göpfert, Heiko Wersing, Barbara Hammer
Deep convolutional neural networks have achieved great successes over recent years, particularly in the domain of computer vision. They are fast, convenient, and -- thanks to matur…
Adversarial attacks hidden in plain sight
Jan Philip Göpfert, André Artelt, Heiko Wersing +1
Convolutional neural networks have been used to achieve a string of successes during recent years, but their lack of interpretability remains a serious issue. Adversarial examples…
Optimum Reject Options for Prototype-based Classification
Lydia Fischer, Barbara Hammer, Heiko Wersing
We analyse optimum reject strategies for prototype-based classifiers and real-valued rejection measures, using the distance of a data point to the closest prototype or probabilisti…