A SAM-adapted weakly-supervised semantic segmentation method constrained by uncertainty and transformation consistency
Semantic segmentation of remote sensing imagery is a fundamental task to generate pixel-wise category maps. Existing deep learning networks rely heavily on dense pixel-wise labels, incurring high acquisition costs. Given this challenge, this study introduces sparse point labels, a type of cost-effec...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000871 |
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