使用无人机图像和人工智能技术绘制杂草地图:当前的趋势和挑战
Maurício Cagliari Tosin1, Aldo Merotto Júnior1, Estéfani Sulzbach1
1Crop Science Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil.
Pest management science
|August 21, 2025
概括
通过无人机成像在农业中实时识别杂草. 这篇评论分析了用于杂草测绘的机器学习方法,强调了精准农业的挑战和未来方向.
科学领域:
- 农业工程
- 计算机科学
- 遥感技术
背景情况:
- 无人驾驶飞行器 (UAV) 在识别杂草方面具有很高的准确性 (>90%).
- 在嵌入式系统上实时识别杂草仍然是一个挑战.
- 基于无人机的杂草测绘对于精准农业至关重要.
研究的目的:
- 通过无人机成像审查和分析用于杂草识别的机器学习和深度学习 (DL) 应用.
- 突出目前研究的方法,挑战和优势/局限性.
- 以指导未来的实时杂草测绘和特定场所的除草剂应用研究.
主要方法:
- 对基于无人机的杂草识别学术研究进行系统的文献审查.
- 根据方法和所涉及的问题组织和比较研究.
- 对特征提取和分类的经典和DL方法的分析.
主要成果:
- 经典方法侧重于光谱,纹理和几何特征,并倾向于非可见光谱.
- DL方法擅长直接从图像中自动提取多尺度的特征.
- 对于区分杂草物种和类型,DL显得非常有前途.
结论:
- 无人机图像与DL相结合提供了强大的杂草绘图方法.
- 需要进一步的研究来克服实时嵌入式系统的挑战.
- 这次审查为开发特定场所的杂草管理智能系统提供了洞察力.
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