DETECTION OF DISEASES IN ARECANUT LEAVES USING YOLOv8

Abstract: Monitoring plant health and finding plant diseases are essential for sustainable agriculture. Disease identification and preventative strategies are a significant challenge because of the rapid rise in a variety of diseases and the low level of knowledge of these ailments. Early discovery gives more time to implement the proper preventative measures. Since arecanut plants are very vulnerable to a variety of pests and diseases, the suggested method is used to identify arecanut leaf diseases and divide them into four groups: healthy, diseased leaves with yellow spots, leaf blight, and yellow leaves. The project main goal is to create a YOLO model that analyses leaf images and can be used to find plant diseases.

Keywords: YOLO, Dataset, Epochs, Pixels.