14 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.CV2022
Simplified Learning of CAD Features Leveraging a Deep Residual Autoencoder
Raoul Schönhof, Jannes Elstner, Radu Manea +3
In the domain of computer vision, deep residual neural networks like EfficientNet have set new standards in terms of robustness and accuracy. One key problem underlying the trainin…
cs.GR2022★ 4 cited
Towards automated Capability Assessment leveraging Deep Learning
Raoul Schönhof, Manuel Fechter
Aiming for a higher economic efficiency in manufacturing, an increased degree of automation is a key enabler. However, assessing the technical feasibility of an automated assembly…
cs.AI2022★ 14 cited
Feature Visualization within an Automated Design Assessment leveraging Explainable Artificial Intelligence Methods
Raoul Schönhof, Artem Werner, Jannes Elstner +3
Not only automation of manufacturing processes but also automation of automation procedures itself become increasingly relevant to automation research. In this context, automated c…