Ma. Kristin Agbulos, Yovito Sarmiento, J. Villaverde
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引用次数: 15
摘要
稻瘟病和褐斑病是影响水稻种植的主要病害。水稻病害的监测和防治对调控水稻生产具有重要意义。在这项研究中,关键目标是开发一种应用程序,以确定水稻叶片是否有叶瘟病或褐斑病。该系统的开发采用了You Only Look Once (YOLO)算法。YOLO算法使用200张水稻叶片图像的自定义数据集进行训练。结果表明,该装置对叶瘟病的检测准确率为90.00%,对2类褐斑病的检测准确率为70.00%。对于第三类,即未知疾病,该设备的性能导致了100.00%的准确率。因此,该装置的总体精度为73.33%,调试误差仅为26.67%。
Identification of Leaf Blast and Brown Spot Diseases on Rice Leaf with YOLO Algorithm
Rice Leaf Blast Disease and Brown Spot Disease are among the most significant diseases affecting rice cultivation. Monitoring and maintaining rice plants from many diseases are very important to regulate their production. In this study, the key objective was to develop an application that identifies whether a rice leaf has leaf blast or brown spot disease. The You Only Look Once (YOLO) Algorithm was implemented for the development of the system. The YOLO algorithm was trained with a custom dataset of 200 rice leaf images. It was found out that the device’s accuracy for leaf blast disease was 90.00% while the class 2 brown spot disease was at 70.00%. For the third class, which was the unknown disease, the device’s performance resulted in a 100.00% of accuracy. Therefore, it was concluded that the overall accuracy of the device was at 73.33% and the error of commission was only 26.67%.