IDADP-葡萄病害识别研究图像数据集

Building an image dataset for machine learning modeling is very important for efficiently identifying agricultural diseases and pests. Therefore, we have constructed an image dataset for agricultural diseases and pests research (IDADP) which covers such aspects of agricultural diseases and pests as image acquisition, classification, labeling, storage and modeling. Meanwhile, this image dataset provides online diagnosis of agricultural diseases and related technical consultation services for scholars and agricultural technicians. The grape disease dataset has about 45.4 GB, and 7 high-quality disease images such as powdery mildew and downy mildew, a total of 3622 images. As a standard dataset for machine learning modeling in large data environment, this image dataset will provide valuable basic data resources. And it has important applicability in promoting the development of agricultural disease identification.构建面向机器学习建模的图像数据集，对于高效识别农业病虫害具有重要意义。为此，我们搭建了农业病虫害研究图像数据集（Image Dataset for Agricultural Diseases and Pests, IDADP），该数据集覆盖农业病虫害领域的图像采集、分类、标注、存储与建模等全流程环节。与此同时，本数据集还可为学者与农业技术人员提供农业病害在线诊断及相关技术咨询服务。本数据集包含的葡萄病害子数据集容量约为45.4 GB，涵盖白粉病、霜霉病等7类优质病害图像，总计3622张。作为适配大数据环境下机器学习建模的标准数据集，本图像数据集将提供极具价值的基础数据资源，在推动农业病害识别技术发展方面具备重要应用价值。

搜集汇总

背景与挑战

背景概述

该数据集是一个包含3622张葡萄病害图像的集合，涵盖7种病害类型，适用于机器学习建模和农业病害识别研究。数据集由中国科学院合肥物质科学研究院发布，数据量为696.96 MB，具有重要的农业应用价值。