Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution

K. Velumani, R. Lopez-Lozano, S. Madec, W. Guo, J. Gillet, A. Comar, F. Baret

Open source

DOI: 10.34133/2021/9824843
Published: 2021
Container: Plant Phenomics
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.34133/2021/9824843,
  title = {Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution},
  author = {K. Velumani and R. Lopez-Lozano and S. Madec and W. Guo and J. Gillet and A. Comar and F. Baret},
  year = {2021},
  journal = {Plant Phenomics},
  doi = {10.34133/2021/9824843},
  url = {https://doi.org/10.34133/2021/9824843}
}

RIS

TY  - JOUR
TI  - Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution
AU  - K. Velumani
AU  - R. Lopez-Lozano
AU  - S. Madec
AU  - W. Guo
AU  - J. Gillet
AU  - A. Comar
AU  - F. Baret
PY  - 2021
JO  - Plant Phenomics
DO  - 10.34133/2021/9824843
UR  - https://doi.org/10.34133/2021/9824843
ER  -

APA

Velumani, K., Lopez-Lozano, R., Madec, S., Guo, W., Gillet, J., Comar, A., & Baret, F. (2021). Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution. Plant Phenomics. https://doi.org/10.34133/2021/9824843

Source records

crossref · retrieved 2026-09-26T04:43:20.011Z