A segment anything model-based geological remote sensing interpretation method with a distributed data-parallel deep learning framework
The interpretation of remote sensing images is pivotal in extracting geological elements of interest. Recent studies using deep learning models often fail to provide accurate boundaries between geological elements due to high interclass similarity and imbalanced data distribution. Furthermore, these...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2542913 |
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