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BGR-net: A boundary-guided refinement network for multi-class cloud detection
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DOI：10.1016/j.rsase.2026.102024.png)
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摘要
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• 提出了BGR-Net，一种用于多类云检测的混合CNN-Transformer模型。 • 引入了自适应门控融合以增强判别特征。 • 在Himawari-9影像上实现了优越的mIoU（68.37%）和F1-score（81.21%）。 • 显著降低了计算开销（GFLOPs）以实现实时监测。 • 展示了对薄云和碎片化云边界的鲁棒检测能力。
Keyword:
BGR-Net
cloud detection
CNN-Transformer hybrid
adaptive gating fusion
boundary-guided refinement
期刊
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论文数:
261
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