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We sincerely thank the authors of [SAM3](https://github.com/facebookresearch/sam3) and [UniMatch](https://github.com/LiheYoung/UniMatch) for their excellent open‑source work, and we also thank the contributors of the publicly available [DeepGlobe](https://www.kaggle.com/datasets/balraj98/deepglobe-land-cover-classification-dataset?spm=5176.28103460.0.0.96a02988pIA0pI) and [Potsdam](https://www.isprs.org/resources/datasets/benchmarks/UrbanSemLab/2d-sem-label-potsdam.aspx?utm_source=chatgpt.com) datasets. Please follow the licenses and terms of the original models and datasets.
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# Acknowledgments
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We sincerely thank the authors of [SAM3](https://github.com/facebookresearch/sam3) and [UniMatch](https://github.com/LiheYoung/UniMatch) for their excellent open‑source work, and we also thank the contributors of the publicly available [DeepGlobe](https://www.kaggle.com/datasets/balraj98/deepglobe-land-cover-classification-dataset?spm=5176.28103460.0.0.96a02988pIA0pI) and [Potsdam](https://www.isprs.org/resources/datasets/benchmarks/UrbanSemLab/2d-sem-label-potsdam.aspx?utm_source=chatgpt.com) datasets. Please follow the licenses and terms of the original models and datasets.
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