Lightweight deep learning for tomato disease detection: trends, challenges, and edge AI perspectives.

Gunasekaran H, Rajkumar S, Kirubhadharsini B L

DOI: 10.3389/fpls.2025.1737208
Published: 2025
Container: Frontiers in plant science
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fpls.2025.1737208,
  title = {Lightweight deep learning for tomato disease detection: trends, challenges, and edge AI perspectives.},
  author = {Gunasekaran H and Rajkumar S and Kirubhadharsini B L},
  year = {2025},
  journal = {Frontiers in plant science},
  doi = {10.3389/fpls.2025.1737208},
  url = {https://doi.org/10.3389/fpls.2025.1737208}
}

RIS

TY  - JOUR
TI  - Lightweight deep learning for tomato disease detection: trends, challenges, and edge AI perspectives.
AU  - Gunasekaran H
AU  - Rajkumar S
AU  - Kirubhadharsini B L
PY  - 2025
JO  - Frontiers in plant science
DO  - 10.3389/fpls.2025.1737208
UR  - https://doi.org/10.3389/fpls.2025.1737208
ER  -

APA

H, G., S, R., & L, K. B. (2025). Lightweight deep learning for tomato disease detection: trends, challenges, and edge AI perspectives.. Frontiers in plant science. https://doi.org/10.3389/fpls.2025.1737208

Source records

pubmed · retrieved 2026-09-25T03:32:32.864Z