4 citations · 8 across the 9 of their papers we have counts for
4 papers · 1 filter
Data-driven Modeling in Metrology -- A Short Introduction, Current Developments and Future Perspectives
Linda-Sophie Schneider, Patrick Krauss, Nadine Schiering +3
Mathematical models are vital to the field of metrology, playing a key role in the derivation of measurement results and the calculation of uncertainties from measurement data, inf…
The Artificial Neural Twin -- Process Optimization and Continual Learning in Distributed Process Chains
Johannes Emmert, Ronald Mendez, Houman Mirzaalian Dastjerdi +2
Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge fo…
Deep autofocus with cone-beam CT consistency constraint
Alexander Preuhs, Michael Manhart, Philipp Roser +5
High quality reconstruction with interventional C-arm cone-beam computed tomography (CBCT) requires exact geometry information. If the geometry information is corrupted, e. g., by…
Learning with Known Operators reduces Maximum Training Error Bounds
Andreas K. Maier, Christopher Syben, Bernhard Stimpel +7
We describe an approach for incorporating prior knowledge into machine learning algorithms. We aim at applications in physics and signal processing in which we know that certain op…