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.
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EV-CLIP introduces mask and context visual prompts to adapt CLIP for improved few-shot video action recognition under visual challenges such as low light and egocentric views, outperforming other efficient methods with backbone-scale-independent efficiency.
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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.
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EV-CLIP: Efficient Visual Prompt Adaptation for CLIP in Few-shot Action Recognition under Visual Challenges
EV-CLIP introduces mask and context visual prompts to adapt CLIP for improved few-shot video action recognition under visual challenges such as low light and egocentric views, outperforming other efficient methods with backbone-scale-independent efficiency.