International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 3 May-June 2024 Submit your research before last 3 days of June to publish your research paper in the issue of May-June.

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
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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