ESP Journal of Engineering & Technology Advancements |
© 2023 by ESP JETA |
Volume 3 Issue 1 |
Year of Publication : 2023 |
Authors : Umesh D Shirale, Ajij Sayyad |
:10.56472/25832646/JETA-V3I2P105 |
Umesh D Shirale, Ajij Sayyad, 2023. "Classification of Potato Plant Leaf Diseases Using Convolution Neural Networks ESP Journal of Engineering & Technology Advancements 3(1): 98-106.
One of the most common food crops grown worldwide is the potato. Numerous diseases prevent potato plants from growing properly. This plant's leaf area has observable illnesses. Early Blight (EB) and Late Blight are two prevalent leaf ailments that affect potato plants (LB). To improve the yield of this crop, it would be very beneficial if these diseases were discovered early on. Image processing is the greatest solution for resolving this issue by identifying and assessing these disorders. The system to identify and categorize potato leaf diseases proposed in this paper is based on deep learning and image processing. The 2152 images of healthy and diseased potato leaves utilized in this study were collected from the publicly accessible Plant Village database. Convolution neural networks were employed for object recognition, and logistic regression was used to accurately classify diseased from healthy leaves. Our suggested strategy results in a path for automatic plant leaf disease detection.
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Potato diseases, Late blight, Early blight, CNN