Artificial Intelligence-Driven Plant Disease Detection and Diagnosis: A Comprehensive Review of Deep Learning Approaches, Multimodal Sensing Technologies, and Future Perspectives in Precision Agriculture
- DOI
- 10.5423/ppj.rw.01.2026.0004
- Published
- 2026-04-01
- Container
- The Plant Pathology Journal
- Publisher
- Korean Society of Plant Pathology
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.5423/ppj.rw.01.2026.0004,
title = {Artificial Intelligence-Driven Plant Disease Detection and Diagnosis: A Comprehensive Review of Deep Learning Approaches, Multimodal Sensing Technologies, and Future Perspectives in Precision Agriculture},
author = {Surakshya Ghimire and Rajan Lamsal and Anvesh Sankuratri and Pradeep Lakkarsu and Sairam Vutla},
year = {2026},
journal = {The Plant Pathology Journal},
doi = {10.5423/ppj.rw.01.2026.0004},
url = {https://doi.org/10.5423/ppj.rw.01.2026.0004}
}RIS
TY - JOUR TI - Artificial Intelligence-Driven Plant Disease Detection and Diagnosis: A Comprehensive Review of Deep Learning Approaches, Multimodal Sensing Technologies, and Future Perspectives in Precision Agriculture AU - Surakshya Ghimire AU - Rajan Lamsal AU - Anvesh Sankuratri AU - Pradeep Lakkarsu AU - Sairam Vutla PY - 2026 JO - The Plant Pathology Journal DO - 10.5423/ppj.rw.01.2026.0004 UR - https://doi.org/10.5423/ppj.rw.01.2026.0004 ER -
APA
Ghimire, S., Lamsal, R., Sankuratri, A., Lakkarsu, P., & Vutla, S. (2026). Artificial Intelligence-Driven Plant Disease Detection and Diagnosis: A Comprehensive Review of Deep Learning Approaches, Multimodal Sensing Technologies, and Future Perspectives in Precision Agriculture. The Plant Pathology Journal. https://doi.org/10.5423/ppj.rw.01.2026.0004
Source records
- crossref · retrieved 2026-09-26T14:07:38.246Z