Plant Leaf Disease Detection using Deep Learning
Keywords:
Convolutional Neural Network (CNN), Leaf disease, Powdery, ReLU, Rule-based, RustAbstract
This paper exploits the latest deep learning technologies in developing an efficient and accurate plant disease detection system. Convolutional Neural Networks applied in this system can support the identification of various plant diseases from their leaf images. Around 1532 images of healthy and diseased leaf images are collected. The methodology development involves creating a comprehensive dataset of plant leaves with classified diseases and proposing CNN architecture and trained model to detect diseases in new leaf images. This provides an accurate diagnosis with causes, symptoms, and disease prevention measures. Farmers can use the developed methodology through an app to detect leaf disease in its early stages and protect their crops from infection. An overall accuracy of 92.5% is obtained.
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