基于高光谱和RGB图像的玉米种子数据集
Chao Li1, Chen Zhang1, Wenbo Zhang2
1School of Information Engineering, Xinxiang Institute of Engineering, Xinxiang, Henan Province 453003, China.
Data in brief
|February 2, 2026
概括
本研究引入了一套用于玉米种子分析的多式数据集,使用高光谱和RGB成像. 这些数据支持种子品种分类和精准农业应用.
科学领域:
- 农业科学 农业科学
- 计算机视觉 计算机视觉
- 数据科学数据科学数据科学
背景情况:
- 准确的玉米种子表征对于农业生产率至关重要.
- 多模式成像为表型分析提供了增强的数据.
- 开发强大的数据集对于农业中的机器学习至关重要.
研究的目的:
- 通过使用高光谱和RGB成像,创建玉米种子的综合数据集.
- 促进种子品种分类和表型分析方面的研究.
- 支持精准农业和机器学习方面的进步.
主要方法:
- 使用HY-6010-S高光谱成像系统 (400-1000nm) 和RGB工业摄像头.
- 从12个品种的大约2400个玉米种子样本获得了多式联络数据.
- 使用HIT软件和Python应用预处理技术,包括降低噪音,删除背景和带选择.
主要成果:
- 创建了一个大规模的多式联运数据集,模拟玉米种子的表型分析.
- 该数据集包括用于详细描述种子特征的光谱和视觉信息.
- 数据处理确保了下游应用的准确性和可靠性.
结论:
- 开发的数据集对于种子品种分类和表型分析有价值.
- 这一资源将促进精准农业中的机器学习应用.
- 多模式成像为农业数据采集提供了强大的方法.
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