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In-line holographic droplet imaging: accelerated classification with convolutional neural networks and quantitative experimental validation.

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Title: In-line holographic droplet imaging: accelerated classification with convolutional neural networks and quantitative experimental validation.
Authors: Thiede, Birte1,2 (AUTHOR), Schlenczek, Oliver2 (AUTHOR), Stieger, Katja1,2 (AUTHOR), Ecker, Alexander2,3 (AUTHOR), Bodenschatz, Eberhard1,2,4 (AUTHOR), Bagheri, Gholamhossein2 (AUTHOR) gholamhossein.bagheri@ds.mpg.de
Source: Atmospheric Measurement Techniques. 2025, Vol. 18 Issue 21, p6291-6314. 24p.
Database: Academic Search Ultimate
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ISSN:18671381
DOI:10.5194/amt-18-6291-2025