Plant Disease Detection

Abstract

Plant disease classification plays a crucial role in the early detection and management of diseases affecting crops. This abstract highlights the use of machine learning techniques, specifically convolutional neural networks, for accurate and automated plant disease classification. By leveraging diverse datasets of plant images, pre-processing techniques, and training algorithms, these models enable real-time disease identification. The integration of these models into user-friendly mobile or web applications empowers farmers and gardeners to swiftly diagnose plant diseases and implement appropriate treatments. This approach holds great promise for enhancing agricultural practices, minimizing crop losses, and ensuring global food security through timely disease management.