Unlocking the capabilities of explainable few‑shot learning in remote sensing
Recent advancements have significantly improved the efficiency and effectiveness of deep learning methods for image-based remote sensing tasks. However, the requirement for large amounts of labeled data can limit the applicability of deep neural networks to existing remote sensing datasets. To ov...
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Main Authors: | , , , , |
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格式: | Article |
語言: | English |
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2024
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在線閱讀: | https://hdl.handle.net/10356/178366 |
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