Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 8 No 3 (2024): Volume 8, Issue 3, March 2024 | Pages: 323-327
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 17-04-2024
Crop disease diagnosis is very crucial task for every farmer and individual in order to prevent various losses like less productivity, less quality and quantity or it can also lead to defective yield. Therefore, early identification and early detection can help to save the crop yield. Agricultural productivity is something on which economy highly depends. This is one of the reasons that diseases detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. Manual diagnosis of plant diseases needs expert knowledge along with awareness. So, automatic diseases detection and identification of plants by application of computer vision approaches is of utmost importance. In this system, different computer vision approaches for plant diseases detection are analyzed. The results demonstrate the effectiveness of various methods in leaf disease detection.
Leaf disease detection, Image processing, Segmentation, Feature extraction, Convolutional Neural Networks, CNN
Rohan Bhosale, Aniket Paul, Sahil Shinde, Prof. Pooja Menon, “Plant Leaf Disease Detection and Classification Using CNN”, Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 8, Issue 3, pp 323-327, March 2024. Article DOI https://doi.org/10.47001/IRJIET/2024.803049
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