Rust is a severe disease affecting many productive plant leaf regions. It is caused by pathogenic fungi that attack the underside of plant leaf and it is characterized by the presence of yellow-orange and powdery points. If not treated, rust can cause a drop in coffee production of up to 45%. In this sense, this paper presents a contribution to the problem of rust identification that doesn’t use “handcrafted” features, i.e., features extracted according to rules established by human programmers. Instead, we propose to train a yolo algorithm to learn to identify rust infection. We evaluated our yolo algorithm in a set of images provided by an expert and comparison results show that our approach is able to detect the infection with a high precision, as corroborated by the high Dice coefficient obtained.
Keyword : CNN, YOLOv5, Image Processing, Deep Learning, Object Detection.