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- Plant disease diagnosis is a huge issue in increasing the production of yield in the agriculture sector. Identifying plant diseases is crucial to prevent loss of yield and quantity of agricultural products. The recent advances in computer vision help researchers use artificial intelligence technology to find and detect the type of plant disease in crops. In this current research, a deep learning technology is used for detecting and classifying the type of disease through an image processing technique. Convolutional Neural Network (CNN) is utilized for image processing to detect diseases, including image acquisition, image preprocessing, image segmentation, feature extraction and classification. This describes a method for detecting the disease of plants by using the image of their leaves. It also describes the algorithm for extracting some segmentation and functionality used in the detection of plant diseases.
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Cite Article:
"PREDICTING CROP HEALTH USING CNN’s ALGORITHM ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b986-b992, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504223.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator