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Editor: @Kevin-Mattheus-Moerman (all papers)
Reviewers: @imagejan (all reviews), @ajasja (all reviews)
Authors
Hélène Kabbech (0000-0002-9200-2112), Ihor Smal (0000-0001-7576-7028)
Citation
Kabbech et al., (2024). TrackSegNet: a tool for trajectory segmentation into diffusive states using supervised deep learning. Journal of Open Source Software, 9(98), 6157, https://doi.org/10.21105/joss.06157
@article{Kabbech2024,
doi = {10.21105/joss.06157},
url = {https://doi.org/10.21105/joss.06157},
year = {2024},
publisher = {The Open Journal},
volume = {9},
number = {98},
pages = {6157},
author = {Hélène Kabbech and Ihor Smal},
title = {TrackSegNet: a tool for trajectory segmentation into diffusive states using supervised deep learning},
journal = {Journal of Open Source Software}
}
Tags
single-particle tracking trajectory segmentation supervised deep learning mean squared displacement
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This work is licensed under a Creative Commons Attribution 4.0 International License.
