海事地图:海底和空中海洋图像的协作数据集
Matteo Contini1,2, Victor Illien3, Mohan Julien3
1IFREMER Délégation Océan Indien (DOI), Le Port, 97420, La Réunion, Rue Jean Bertho, France. matteo.contini@ifremer.fr.
Scientific data
|January 14, 2025
概括
公民科学倡议正在利用来自印度洋西南部的160多万张水下和空中图像绘制海洋生物多样性的地图. 这种有价值的,公开可访问的数据集有助于人工智能模型培训环境研究.
科学领域:
- 海洋生物学 海洋生物学
- 环境科学 环境科学
- 公民科学 公民科学
背景情况:
- 绘制海洋生物多样性的地图对于环境研究至关重要,但也带来了重大挑战.
- 公民科学倡议为全球规模和高分辨率的数据收集提供了一个可扩展的解决方案.
研究的目的:
- 描述用于海洋生物多样性研究的大量定期更新的水下和空中图像数据集.
- 促进公民收集的数据用于训练人工智能 (AI) 模型的使用.
- 促进海洋研究中的数据共享和互操作性.
主要方法:
- 采集了超过160万个地理位置的水下和空中图像,这些图像是在浅热带沿海地区使用低成本平台收集的.
- 利用公民和研究人员操作的动作摄像头,从而产生异质的图像质量.
- 用于人工智能模型培训的51个不同的类 (例如动物,息地) 的注释图像.
- 通过DOI分配和通过社区标准实现互操作性来确保数据的可发现性.
主要成果:
- 现在可以获得来自印度洋西南部160多万张图像的大量数据集.
- 数据集包括地理位置图像,其中一个子集为人工智能培训进行注释.
- 不同质的图像质量反映了水下图像识别的现实世界挑战.
结论:
- 公民科学与人工智能相结合,可以显著推进海洋生物多样性测绘.
- 描述的数据集和开源工作流程能够为海洋研究做出更广泛的贡献.
- 标准化数据实践提高了公民科学数据的价值和可重复使用性.
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