7 citations · 16 across the 20 of their papers we have counts for
3 papers · 1 filter
Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing
Andreas Alpers, Orkun Furat, Christian Jung +4
This paper reviews algorithmic and modeling approaches for fitting generalized power diagrams to three-dimensional image data, a key step in virtual materials testing (VMT). Beyond…
Determination of droplet size from wide-angle light scattering image data using convolutional neural networks
Tom Kirstein, Simon Aßmann, Orkun Furat +2
Wide-angle light scattering (WALS) offers the possibility of a highly temporally and spatially resolved measurement of droplets in spray-based methods for nanoparticle synthesis. T…
Using convolutional neural networks for stereological characterization of 3D hetero-aggregates based on synthetic STEM data
Lukas Fuchs, Tom Kirstein, Christoph Mahr +5
The structural characterization of hetero-aggregates in 3D is of great interest, e.g., for deriving process-structure or structure-property relationships. However, since 3D imaging…