Plant Detection in RGB Images from Unmanned Aerial Vehicles Using Segmentation by Deep Learning and an Impact of Model Accuracy on Downstream Analysis.
- DOI
- 10.3390/jimaging11010028
- Published
- 2025 Jan 20
- Container
- Journal of imaging
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/jimaging11010028,
title = {Plant Detection in RGB Images from Unmanned Aerial Vehicles Using Segmentation by Deep Learning and an Impact of Model Accuracy on Downstream Analysis.},
author = {Kozhekin MV and Genaev MA and Komyshev EG and Zavyalov ZA and Afonnikov DA},
year = {2025},
journal = {Journal of imaging},
doi = {10.3390/jimaging11010028},
url = {https://doi.org/10.3390/jimaging11010028}
}RIS
TY - JOUR TI - Plant Detection in RGB Images from Unmanned Aerial Vehicles Using Segmentation by Deep Learning and an Impact of Model Accuracy on Downstream Analysis. AU - Kozhekin MV AU - Genaev MA AU - Komyshev EG AU - Zavyalov ZA AU - Afonnikov DA PY - 2025 JO - Journal of imaging DO - 10.3390/jimaging11010028 UR - https://doi.org/10.3390/jimaging11010028 ER -
APA
MV, K., MA, G., EG, K., ZA, Z., & DA, A. (2025). Plant Detection in RGB Images from Unmanned Aerial Vehicles Using Segmentation by Deep Learning and an Impact of Model Accuracy on Downstream Analysis.. Journal of imaging. https://doi.org/10.3390/jimaging11010028
Source records
- pubmed · retrieved 2026-11-10T07:38:55.452Z