Integrated Framework for Unsupervised Building Segmentation with Segment Anything Model-Based Pseudo-Labeling and Weakly Supervised Learning
The Segment Anything Model (SAM) has had a profound impact on deep learning applications in remote sensing. SAM, which serves as a prompt-based foundation model for segmentation, exhibits a remarkable capability to “segment anything,” including building objects on satellite or airborne images. To fa...
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| Egile Nagusiak: | , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
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MDPI AG
2024-01-01
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| Saila: | Remote Sensing |
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| Sarrera elektronikoa: | https://www.mdpi.com/2072-4292/16/3/526 |
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