BDD-Net: A General Protocol for Mapping Buildings Damaged by a Wide Range of Disasters Based on Satellite Imagery

BDD-Net: A General Protocol for Mapping Buildings Damaged by a Wide Range of Disasters Based on Satellite Imagery

The timely and accurate recognition of damage to buildings after destructive disasters is one of the most important post-event responses. Due to the complex and dangerous situations in affected areas, field surveys of post-disaster conditions are not always feasible. The use of satellite imagery for...

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Bibliographic Details
Main Authors: Jinyuan Shao, Lina Tang, Ming Liu, Guofan Shao, Lang Sun, Quanyi Qiu
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
disaster assessment
building detection
building damage
remote sensing
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/2072-4292/12/10/1670

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