The implementation of particle-tracking techniques with deep neural networks is a promising way to determine particle motion within complex flow structures. A graph neural network-enhanced method enables accurate particle tracking by significantly reducing the number of lost trajectories.
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Atis, S., Agostini, L. Catching up with missing particles. Nat Mach Intell 6, 13–14 (2024). https://doi.org/10.1038/s42256-023-00770-x
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DOI: https://doi.org/10.1038/s42256-023-00770-x
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