Detection of brown spot and leaf blight in rice with the You Only Look Once (YOLO) algorithm
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Abstract
Rice is a plant that produces rice as the staple food for almost all Indonesians. Rice plays a vital role in the food chain in Indonesia. However, many types of diseases on rice leaves attack and inhibit the growth of rice in Indonesian rice fields. Among them are brown spots and leaf blight. So far, the classification of diseases on rice leaves is only based on the experience of farmers. This results in uncertainty and diagnostic inaccuracy in classifying various diseases on rice plants. In this case, a method is needed to solve the problem. The method used in this research is digital imagery by processing images of diseases on the leaves of rice plants using the YOLO (You Only Look Once) algorithm. YOLO uses a single Convolutional Neural Network (CNN) for object classification and localization using Bounding Box. This research aims to provide options to users in determining the diagnosis of leaf spots and blight diseases on the leaves of rice plants. The average Precision (mAP) evaluation result is 69%, indicating that this method is suitable for detecting diseases on rice leaves.
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