Automatic Detection and Image Recognition of Precision Agriculture for Citrus Diseases

ChauChung Song, Chih-Heng Wang, Yifeng Yang
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引用次数: 10

Abstract

In recent years, the development of precision agriculture is a new technology. The main reason for the automation of agricultural processes is to save the time and energy required to perform repeated farming tasks and to increase production by treating each crop separately and applying smart agricultural concepts. In this paper, an automatic detection and image recognition of citrus diseases is presented that can help farmer find the disease and identify it from the captured images. This method use YOLO(You Only Look Once) algorithm which is an object detection model to detect and recognize the diseases from citrus leaf images. YOLO can realtime detect the disease and circle around it on the image and video. The dataset includes images of citrus leaf with two kinds of diseases: Citrus Canker, Citrus Greening.
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柑橘病害的精准农业自动检测与图像识别
精准农业是近年来发展起来的一门新技术。农业过程自动化的主要原因是为了节省执行重复耕作任务所需的时间和精力,并通过分别处理每种作物和应用智能农业概念来提高产量。本文提出了一种柑橘病害的自动检测与图像识别方法,可以帮助农民从采集的图像中发现病害并进行识别。该方法采用YOLO(You Only Look Once)算法作为目标检测模型,对柑橘叶片图像中的病害进行检测和识别。YOLO可以实时检测疾病,并在图像和视频上绕圈。该数据集包括柑橘叶片的两种病害图像:柑橘溃疡病和柑橘绿化。
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