Revolutionizing building damage detection: A novel weakly supervised approach using high-resolution remote sensing images

Revolutionizing building damage detection: A novel weakly supervised approach using high-resolution remote sensing images

ABSTRACTRapidly estimating post-disaster building damage via high-resolution remote sensing (HRRS) imagery is essential for initial disaster relief. However, the complex appearance of building damage poses challenges for existing methods. Specifically, relying solely on post-disaster images lacks bu...

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Bibliographic Details
Main Authors: Wenfan Qiao, Li Shen, Qi Wen, Quan Wen, Shiyang Tang, Zhilin Li
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:International Journal of Digital Earth
Subjects:
Convolutional neural network
superpixel segmentation
weakly supervised semantic segmentation
high-resolution remote sensing image
building damage detection
Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2023.2298245

Internet

https://www.tandfonline.com/doi/10.1080/17538947.2023.2298245

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