RADA achieves state-of-the-art barely-supervised 3D medical image segmentation by using a region-aware dual-encoder pre-trained on Alpha-CLIP within a triple-view training framework on LA2018, KiTS19 and LiTS datasets.
V-net: Fully convolutional neural networks for volumetric medical image segmentation
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MAG-Net integrates radar dynamics with satellite IR, WV, and BTD channels via dual-stream encoding and uncertainty-weighted decoding to raise CSI40 by 0.083 over prior baselines for intense convective events.
citing papers explorer
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RADA: Region-Aware Dual-encoder Auxiliary learning for Barely-supervised Medical Image Segmentation
RADA achieves state-of-the-art barely-supervised 3D medical image segmentation by using a region-aware dual-encoder pre-trained on Alpha-CLIP within a triple-view training framework on LA2018, KiTS19 and LiTS datasets.
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MAG-Net: Physics-Aware Multi-Modal Fusion of Geostationary Satellite and Radar for Severe Convective Precipitation Nowcasting
MAG-Net integrates radar dynamics with satellite IR, WV, and BTD channels via dual-stream encoding and uncertainty-weighted decoding to raise CSI40 by 0.083 over prior baselines for intense convective events.