Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

Building Damage Detection Using U-Net with Attention Mechanism from Pre- and Post-Disaster Remote Sensing Datasets

The building damage status is vital to plan rescue and reconstruction after a disaster and is also hard to detect and judge its level. Most existing studies focus on binary classification, and the attention of the model is distracted. In this study, we proposed a Siamese neural network that can loca...

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Bibliographic Details
Main Authors: Chuyi Wu, Feng Zhang, Junshi Xia, Yichen Xu, Guoqing Li, Jibo Xie, Zhenhong Du, Renyi Liu
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Remote Sensing
Subjects:
building damage
disaster
remote sensing image
Siamese neural network
U-Net
attention mechanism
Online Access:https://www.mdpi.com/2072-4292/13/5/905

Internet

https://www.mdpi.com/2072-4292/13/5/905

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