User profiles for Jan Philip Göpfert
Jan Philip GöpfertBielefeld University Verified email at uni-bielefeld.de Cited by 273 |
[HTML][HTML] Deep learning for understanding satellite imagery: An experimental survey
Translating satellite imagery into maps requires intensive effort and time, especially leading
to inaccurate maps of the affected regions during disaster and conflict. The combination of …
to inaccurate maps of the affected regions during disaster and conflict. The combination of …
Classification of motor errors to provide real-time feedback for sports coaching in virtual reality—A case study in squats and Tai Chi pushes
For successful fitness coaching in virtual reality, movements of a trainee must be analyzed in
order to provide feedback. To date, most coaching systems only provide coarse information …
order to provide feedback. To date, most coaching systems only provide coarse information …
[PDF][PDF] Deep learning for understanding satellite imagery: An experimental survey. Front
Translating satellite imagery into maps requires intensive effort and time, especially leading
to inaccurate maps of the affected regions during disaster and conflict. The combination of …
to inaccurate maps of the affected regions during disaster and conflict. The combination of …
Why robots should be technical: Correcting mental models through technical architecture concepts
L Hindemith, JP Göpfert, CB Wiebel-Herboth… - Interaction …, 2021 - jbe-platform.com
Research in social robotics is commonly focused on designing robots that imitate human
behavior. While this might increase a user’s satisfaction and acceptance of robots at first glance…
behavior. While this might increase a user’s satisfaction and acceptance of robots at first glance…
Mitigating concept drift via rejection
Learning in non-stationary environments is challenging, because under such conditions the
common assumption of independent and identically distributed data does not hold; when …
common assumption of independent and identically distributed data does not hold; when …
Interpretation of linear classifiers by means of feature relevance bounds
Research on feature relevance and feature selection problems goes back several decades,
but the importance of these areas continues to grow as more and more data becomes …
but the importance of these areas continues to grow as more and more data becomes …
Interpretable locally adaptive nearest neighbors
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 idea …
of data by learning a problem-specific metric. This metric is global. We extend this idea …
[HTML][HTML] Adversarial attacks hidden in plain sight
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 are …
years, but their lack of interpretability remains a serious issue. Adversarial examples are …
Explainable artificial intelligence for improved modeling of processes
In modern business processes, the amount of data collected has increased substantially in
recent years. Because this data can potentially yield valuable insights, automated knowledge …
recent years. Because this data can potentially yield valuable insights, automated knowledge …
Intuitiveness in Active Teaching
JP Göpfert, U Kuhl, L Hindemith… - … on Human-Machine …, 2021 - ieeexplore.ieee.org
While machine learning (ML) gives rise to astonishing results in automated systems, it is
usually at the cost of large data requirements. This makes many successful algorithms from ML …
usually at the cost of large data requirements. This makes many successful algorithms from ML …