Landslide Susceptibility Mapping Considering Landslide Local-Global Features Based on CNN and Transformer
Landslide susceptibility mapping (LSM) is a crucial step in quantitatively assessing landslide risk, essential for geologic hazards prevention. With the rapid development of deep learning models, convolutional neural networks (CNNs), and transformer architectures have been applied to LSM. However, t...
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| Principais autores: | , , , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
IEEE
2024-01-01
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| Serier: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Fag: | |
| Online adgang: | https://ieeexplore.ieee.org/document/10475385/ |
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