Coffee Leaf Disease Identification and Severity Estimation using Deep Learning Methods
This study addresses the challenges faced by the global coffee industry due to the increasing prevalence of coffee plant diseases, which affect the quality and quantity of coffee yield. This research introduces an approach integrating computer vision technology with deep learning models to detect and classify coffee diseases and estimate disease severity. A dataset of 1,086 images from various sources, including Arabica and Robusta coffee leaf images was used. These images, augmented with processing techniques, serve as the foundation for training and evaluating deep learning model, YOLO.