救援网:一个高分辨率的无人机语义细分数据集用于自然灾害损害评估
Maryam Rahnemoonfar1,2, Tashnim Chowdhury3, Robin Murphy4
1Department of Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania, 18015, USA. maryam@lehigh.edu.
Scientific data
|December 20, 2023
概括
"救援网"是一个新的高分辨率数据集,用于评估自然灾害造成的损害. 它提供了详细的像素级注释,以改善使用计算机视觉的救援团队对现场的理解.
科学领域:
- 计算机视觉 计算机视觉
- 深度学习 (Deep Learning) 是一种深度学习.
- 遥感 遥感 遥感 遥感
背景情况:
- 计算机视觉和深度学习方面的进步有助于应对灾害.
- 精确的损害评估对于有效的救援行动至关重要.
研究的目的:
- 介绍RescueNet,一个新的高分辨率灾后数据集.
- 促进对自然灾害后果的全面现场理解.
主要方法:
- 在风迈克尔之后,使用无人机 (UAV) 收集了高分辨率的灾后图像.
- 为所有场景类 (建筑物,道路,树木等) 提供了详细的像素级注释. ) 的情况.
主要成果:
- "救援网"提供了全面的注释,超越了现有的数据集,仅限于特定元素.
- 通过实施最先进的细分模型来证明数据集的实用性.
结论:
- "救援网"加强了对自然灾害损害评估的方法.
- 数据集的详细注释对于改善灾难场景中的现场理解是有价值的.
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