International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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Impact Factor: 9.24
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 6
November-December 2024
Indexing Partners
Machine Learning Framework for Early Detection of Crop Disease
Author(s) | Aditya A H, Amith N P, Anish R Jois, Surya Prakash S P, Naveen Kumar H N |
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Country | India |
Abstract | This review paper looks at recent advancements in crop disease detection through deep learning techniques. Crop diseases significantly lowers agricultural productivity, and accurate diagnosis is essential for effective disease management. In order to identify crop illnesses, the study offers a thorough examination of a number of deep learning models, such as hybrid architectures, recurrent neural networks (RNNs), and convolutional neural networks (CNNs). The prospects, challenges, and future directions of incorporating deep learning for precise and quick crop disease identification are also explained in this research. The insights provided offer hope for the development of sustainable agricultural practices through the application of cutting-edge technologies in disease diagnosis and management. |
Keywords | Deep Learning, Image processing, Leaf disease, Machine Learning, Plant Disease Prediction. |
Field | Engineering |
Published In | Volume 6, Issue 3, May-June 2024 |
Published On | 2024-05-14 |
Cite This | Machine Learning Framework for Early Detection of Crop Disease - Aditya A H, Amith N P, Anish R Jois, Surya Prakash S P, Naveen Kumar H N - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20240 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i03.20240 |
Short DOI | https://doi.org/gtt8s7 |
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E-ISSN 2582-2160
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IJFMR DOI prefix is
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