Plant Disease Detection and Classification by Deep Learning
DOI:
https://doi.org/10.32628/IJSRST25122229Keywords:
Deep learning, plant leaf disease detection, Visualization, small samples, CNN algorithmAbstract
Deep learning has made huge progress, leading to better technology for identifying images. In agriculture, deep learning helps analyze big data and can be very useful in identifying plant diseases. This technology looks at the features of an image to gather information and classify it. Climate change affects plant growth and makes them more likely to get diseases caused by bacteria, viruses, fungi, and other harmful agents. These diseases can slow down plant growth and reduce crop production. The proposed system uses a Convolutional Neural Network (CNN) to detect plant diseases from leaf images. After identifying the disease, it suggests the right pesticide to treat it. The system also provides more details about the disease affecting plants in a specific area.This technology can help farmers decide when to use pesticides. It can also identify which plants are more vulnerable to certain diseases so they can be protected in advance.
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Jyotismita chak, and Dibyajyoti ghosh, “Deep Learning in Leaf Disease Detection”(2014–2024): A Visualization-Based Bibliometric Analysis, Journal Article, computer science bibliography, 10 July 2024.
Md Abu Bakar Laskar, Zhou Jinzhi, Md Mehedi Hasan, Md Tanvin Ashan, “Plant Leaf Disease Detection Using Deep Learning”, LC International Journal of STEM , Volume-05 | Issue-01 | March-2024 .
Yousef Methkal Abd Algani , Orlando Juan Marquez Caro , Liz Maribel Robladillo Bravo , “Leaf disease identification and classification using optimized deep learning”, Journal of International Measurement Confederation, Volume 25, February 2023.
Shital Pawar1, Sakshi Shedge, Nibedita Panigrahi, Jyoti A P, Pradnya Thorave , “Leaf Disease Detection of Multiple Plants Using Deep Learning”, Faridabad, India, The International Conference on Communication, Security and Artificial Intelligence (ICCSAI), 26-27 May 2022 .
Shujuan Zhang, Bin Wang, “Plant Disease Detection and Classification by Deep Learning”, The Inovation Project of Shanxi for Postgraduation, (Volume: 9), 08 April 2021.
H. Tian, T. Wang, Y. Liu, X. Qiao, and Y. Li, ‘‘Computer vision technology in agricultural automation—A review,’’ Inf. Process. Agricult., vol. 7, no. 1, pp. 1–19, 2020.
R. Sujatha, J. M. Chatterjee, N. Jhanjhi, and S. N. Brohi, ‘‘Performance of deep learning vs machine learning in plant leaf disease detection,’’ Microprocessors Microsyst., vol. 80, Feb. 2021, Art. no. 103615.
C. Nguyen, V. Sagan, M. Maimaitiyiming, M. Maimaitijiang, S. Bhadra, and M. T. Kwasniewski, ‘‘Early detection of plant viral disease using hyperspectral imaging and deep learning,’’ Sensors, vol. 21, no. 3, p. 742, Jan. 2021.
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