EFFC-Net: lightweight fully convolutional neural networks in remote sensing disaster images
Continuous development of remote sensing technology can rapidly and accurately extract secondary disaster information, such as the area of various disasters. However, in the extraction process, some disasters should be initially classified and identified. In view of this concept, a lightweight fully...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-01-01
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| Series: | Geo-spatial Information Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2023.2183145 |
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