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Journal Article

Deep learning in plant phenological research: A systematic literature review

MPS-Authors
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Katal,  Negin
Flora Incognita, Dr. Jana Wäldchen, Department Biogeochemical Integration, Prof. Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Rzanny,  Michael
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

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Wäldchen,  Jana
Department Biogeochemical Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society;

External Resource

https://doi.org/10.3389/fpls.2022.805738
(Publisher version)

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Fulltext (public)

BGC3843.pdf
(Publisher version), 3MB

Supplementary Material (public)

BGC3843s1.xlsx
(Supplementary material), 31KB

Citation

Katal, N., Rzanny, M., Mäder, P., & Wäldchen, J. (2022). Deep learning in plant phenological research: A systematic literature review. Frontiers in Plant Science, 13: 805738. doi:10.3389/fpls.2022.805738.


Cite as: https://hdl.handle.net/21.11116/0000-000A-1F97-A
Abstract
There is no abstract available