论文标题
水稻作物的早期疾病诊断
Early Disease Diagnosis for Rice Crop
论文作者
论文摘要
许多现有技术提供了由于各种疾病引起的农作物损害的自动估计。但是，早期检测可以防止或减少损害本身的扩展。现有技术在早期检测中的性能有限是缺乏局部信息。相反，我们为每个图像中的每个患病细分市场提出了一个带有注释的数据集。与现有方法不同，我们建议为每个图像的每个段提供局部分类，而不是将图像分类为健康或患病。我们的方法基于面具RCNN，并提供位置以及植物上受感染区域的扩展。因此，可以估计作物的损害扩展。我们的方法在拟议的数据集上获得了总体87.6％的精度，而在没有纳入本地信息的情况下获得的58.4％。
Many existing techniques provide automatic estimation of crop damage due to various diseases. However, early detection can prevent or reduce the extend of damage itself. The limited performance of existing techniques in early detection is lack of localized information. We instead propose a dataset with annotations for each diseased segment in each image. Unlike existing approaches, instead of classifying images into either healthy or diseased, we propose to provide localized classification for each segment of an images. Our method is based on Mask RCNN and provides location as well as extend of infected regions on the plant. Thus the extend of damage on the crop can be estimated. Our method has obtained overall 87.6% accuracy on the proposed dataset as compared to 58.4% obtained without incorporating localized information.
