An Automatic Detection of Citrus Fruits and Leaves Diseases Using Enhanced Convolutional Neural Network-Reference-Cited by-同舟云学术

An Automatic Detection of Citrus Fruits and Leaves Diseases Using Enhanced Convolutional Neural Network

Published:2023-06-19 Issue:3-4 Volume:6 Page:123-134
ISSN:2520-8195
Container-title:Remote Sensing in Earth Systems Sciences
language:en
Short-container-title:Remote Sens Earth Syst Sci

Author:

Shastri Rajveer,Chaturvedi Abhay,Mouleswararao B.,Varalakshmi S.,Prasad G. N. R.,Ram Mylavarapu Kalyan

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Space and Planetary Science,Atmospheric Science,Computers in Earth Sciences,Geography, Planning and Development,Oceanography

Link

https://link.springer.com/content/pdf/10.1007/s41976-023-00086-9.pdf

Reference17 articles.

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2. Dang-Ngoc H, Cao TNM, Dang-Nguyen C (2021) Citrus leaf disease detection and classification using hierarchical support vector machine. 2021 International Symposium on Electrical and Electronics Engineering (ISEE) pp 69–74. https://doi.org/10.1109/isee51682.2021.9418680

3. Khotsathian S, Lamjiak T, Donnua S, Polvichai J (2022) Convolution neural networks backbone model for citrus leaf disease detection. 2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) pp 1–5. https://doi.org/10.1109/jcsse54890.2022.9836298

4. Goyal N, Kumar S, Saraswat M (2022) Detection of Unhealthy citrus leaves using Machine Learning Technique. 2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence) pp 591–595. https://doi.org/10.1109/confluence52989.2022.9734162

5. Ramadhan MI, Suyanto S (2021) Detection of disease in citrus plants through leaf images using a convolutional neural network. 2021 3rd International Conference on Electronics Representation and Algorithm (ICERA) pp 71–76. https://doi.org/10.1109/icera53111.2021.9538757

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