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

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Volume 8 Issue 2
March-April 2026

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Crop Disease Detection Using Convolutional Neural Network

Author(s) Mr. Arun Teja S, Mr. Kumar N, Mr. Gowtham H, Mr. Pavan M, K Ramalakshmi
Country India
Abstract Crop diseases significantly reduce agricultural productivity and threaten food security worldwide. Early detection is essential to control diseases and support sustainable farming. Traditional methods like manual inspection are time-consuming and often inaccurate. Recent advances in deep learning, especially Convolutional Neural Networks (CNN), enable efficient image-based disease detection by identifying features in leaf images. This research proposes a CNN-based model to detect diseases in crops such as tomatoes, potatoes, corn, apples, strawberries, and cherries, achieving high accuracy and effective automated detection.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 2, March-April 2026
Published On 2026-04-01
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E-ISSN 2582-2160
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