Potato Leaf Disease Classification using Deep Learning Technique CNN

In this work, we suggest a unique method that makes use of convolutional neural networks (CNN) to identify potato leaf disease. Our approach makes use of deep learning to precisely identify and categorise a range of illnesses that impact potato leaves. We achieve great levels of accuracy and robustness in disease identification by training the CNN model on a large dataset of healthy and diseased potato leaves. Farmers and agronomists may identify and control illnesses more quickly and automatically with the help of this suggested technique, which will increase crop output and production. Our technique has shown encouraging results through thorough experimentation and validation, indicating its potential for real-world use in agricultural contexts.