Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning-A Comparison between High-End and Low-Cost Multispectral Sensors.

Seiche AT, Wittstruck L, Jarmer T

DOI: 10.3390/s24051544
Published: 2024 Feb 28
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s24051544,
  title = {Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning-A Comparison between High-End and Low-Cost Multispectral Sensors.},
  author = {Seiche AT and Wittstruck L and Jarmer T},
  year = {2024},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s24051544},
  url = {https://doi.org/10.3390/s24051544}
}

RIS

TY  - JOUR
TI  - Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning-A Comparison between High-End and Low-Cost Multispectral Sensors.
AU  - Seiche AT
AU  - Wittstruck L
AU  - Jarmer T
PY  - 2024
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s24051544
UR  - https://doi.org/10.3390/s24051544
ER  -

APA

AT, S., L, W., & T, J. (2024). Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning-A Comparison between High-End and Low-Cost Multispectral Sensors.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s24051544

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pubmed · retrieved 2026-09-24T23:39:22.102Z