用于通过多谱成像检测葡萄园疾病的数据集
Alessio Saccuti1, Filippo Graziosi2, Dario Lodi Rizzini1
1University of Parma, Parco Area delle Scienze 181/A, 43100 Parma, Italy.
Data in brief
|June 19, 2025
概括
这一数据集提供了多谱图像,用于检测葡萄藤疾病,如黄色斑点 (FD) 和Esca (ED). 它支持开发精准农业工具,以便在葡萄园中早期识别疾病.
科学领域:
- 农业科学 农业科学
- 遥感 遥感 遥感 遥感
- 计算机视觉 计算机视觉
背景情况:
- 葡萄藤病Flavescence dorée (FD) 和Esca (ED) 对葡萄种植构成重大威胁.
- 有限的公共数据集可用于对这些葡萄藤病的多谱分析,特别是现场收集的数据.
研究的目的:
- 引入一个新的多光谱图像数据集,用于开发葡萄藤疾病检测算法.
- 促进疾病自动识别和精准农业方面的研究.
主要方法:
- 使用Micasense RedEdge-P摄像头 (六个光谱带) 收集了多光谱图像.
- 从三种葡萄品种 (安塞洛塔,马拉尼,萨拉米诺) 的正面视角捕获了172张图像.
- 包括原始/加工图像,摄像机校准数据和健康注释.
主要成果:
- 一个全面的数据集,包括原始和处理的多谱图像.
- 关于机器学习模型培训的植物卫生条件的详细注释.
- 提供基于Python的数据集利用示例.
结论:
- 该数据集是通过使用多光谱成像来推进葡萄藤疾病的自动检测的宝贵资源.
- 能够进一步研究机器学习,图像处理和精准农业技术.
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