用于发现和分类棕树疾病的受感染棕树叶的数据集
Abdallah Namoun1, Ahmad B Alkhodre1, Adnan Ahmad Abi Sen2
1AI Centre, Faculty of Computer and Information Systems, Islamic University of Madinah, Madinah 42351, Saudi Arabia.
Data in brief
|October 8, 2024
概括
这项研究引入了关于枣树叶疾病的新数据集,其中包括3089张健康和患病叶子的图像. 本资源有助于开发人工智能,用于早期检测和预防手掌感染.
科学领域:
- 农业科学 农业科学
- 植物病理学 植物病理学
- 计算机视觉 计算机视觉
背景情况:
- 枣树种植在干旱地区至关重要,但易受各种疾病影响产量.
- 早期和准确的疾病鉴定对于有效的管理和预防策略至关重要.
- 对棕叶病的现有数据集有限,阻碍了自动诊断工具的开发.
研究的目的:
- 创建和呈现一个全面的,标记图像数据集的枣树叶疾病.
- 促进深度学习模型的培训和验证,用于自动化疾病分类.
- 支持早期检测和管理枣树感染的研究.
主要方法:
- 从沙特阿拉伯的10个农场收集了608张棕树叶的原始图像.
- 在秋季和春季使用智能手机和单反相机拍摄的图像.
- 处理和增强图像以创建3089个标记图像的最终数据集,按疾病类型 (生理,真菌,害虫引起) 分类.
主要成果:
- 开发了一套数据集,涵盖8种类型的枣树叶疾病,包括缺陷 (,,),真菌感染 (黑烧,叶子斑点,虫,拉奇斯),和害虫感染 (parlatoria blanchardi).
- 数据集包括健康棕树叶的图像,用于基线比较.
- 最终的数据集包含3089个经过处理的图像,适合用于训练机器学习模型.
结论:
- 本次发布的数据集是推进自动检测枣树疾病研究的宝贵资源.
- 它可以开发深度学习模型,用于早期识别,帮助预防疾病和作物管理.
- 这项工作有助于通过技术创新来保护枣庄的种植.
关键词:
在美国,CNN是CNN.这是一棵日棕树.深度学习是一种深度学习.图像数据集是一组图像数据集.棕树叶疾病 棕树叶疾病城甲状腺动物群 (Phoenix dactylifera) 是一个有生命的群体.植物叶子的分类植物叶子的分类更多相关视频
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