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Journal Article

Estimating sliding drop width via side-view features using recurrent neural networks

MPS-Authors
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Shumaly,  Sajjad
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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Darvish,  Fahimeh
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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Li,  Xiaomei
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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Kukharenko,  Oleksandra
Dept. Kremer: Polymer Theory, MPI for Polymer Research, Max Planck Society;

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Steffen,  Werner
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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Butt,  Hans-Jürgen
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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Berger,  Rüdiger
Dept. Butt: Physics at Interfaces, MPI for Polymer Research, Max Planck Society;

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s41598-024-62194-w.pdf
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Citation

Shumaly, S., Darvish, F., Li, X., Kukharenko, O., Steffen, W., Guo, Y., et al. (2024). Estimating sliding drop width via side-view features using recurrent neural networks. Scientific Reports, 14(1): 12033. doi:10.1038/s41598-024-62194-w.


Cite as: https://hdl.handle.net/21.11116/0000-000F-684A-A
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