Flooded Infrastructure Change Detection in Deeply Supervised Networks Based on Multi-Attention-Constrained Multi-Scale Feature Fusion

Flooded Infrastructure Change Detection in Deeply Supervised Networks Based on Multi-Attention-Constrained Multi-Scale Feature Fusion

Flood disasters are frequent, sudden, and have significant chain effects, seriously damaging infrastructure. Remote sensing images provide a means for timely flood emergency monitoring. When floods occur, emergency management agencies need to respond quickly and assess the damage. However, manual ev...

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Bibliographic Details
Main Authors: Gang Qin, Shixin Wang, Futao Wang, Suju Li, Zhenqing Wang, Jinfeng Zhu, Ming Liu, Changjun Gu, Qing Zhao
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
change detection
deep learning
multi-scale feature fusion
flooded buildings and roads
very-high-resolution remote sensing images
Online Access:https://www.mdpi.com/2072-4292/16/22/4328
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