Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Třeboň fishponds, Czech Republic.
- DOI
- 10.1016/j.scitotenv.2024.174504
- Published
- 2024 Oct 15
- Container
- The Science of the total environment
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.scitotenv.2024.174504,
title = {Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Třeboň fishponds, Czech Republic.},
author = {Ge Y and Shen F and Sklenička P and Vymazal J and Baxa M and Chen Z},
year = {2024},
journal = {The Science of the total environment},
doi = {10.1016/j.scitotenv.2024.174504},
url = {https://doi.org/10.1016/j.scitotenv.2024.174504}
}RIS
TY - JOUR TI - Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Třeboň fishponds, Czech Republic. AU - Ge Y AU - Shen F AU - Sklenička P AU - Vymazal J AU - Baxa M AU - Chen Z PY - 2024 JO - The Science of the total environment DO - 10.1016/j.scitotenv.2024.174504 UR - https://doi.org/10.1016/j.scitotenv.2024.174504 ER -
APA
Y, G., F, S., P, S., J, V., M, B., & Z, C. (2024). Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Třeboň fishponds, Czech Republic.. The Science of the total environment. https://doi.org/10.1016/j.scitotenv.2024.174504
Source records
- pubmed · retrieved 2026-09-26T02:25:46.666Z
- europe-pmc · retrieved 2026-09-26T02:25:46.690Z