1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2023
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…
cs.CV2023★ 1 cited
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…
stat.AP2023
Multidimensional characterization of particle morphology and mineralogical composition using CT data and R-vine copulas
Orkun Furat, Tom Kirstein, Thomas Leißner +4
Computed tomography (CT) can capture volumes large enough to measure a statistically meaningful number of micron-sized particles with a sufficiently good resolution to allow for th…