A compact morphology-aware U-Net with an astronomy-preservation loss achieves F1 0.978 on synthetic RFI masks, keeps 97.6% of injected dispersed-signal fluence, and runs 6.2-7.0x faster than filtool in compute-only benchmarks.
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MARS: A Lightweight Morphology-Aware RFI Segmentation Network for Mask-Guided Mitigation in Radio Astronomy
A compact morphology-aware U-Net with an astronomy-preservation loss achieves F1 0.978 on synthetic RFI masks, keeps 97.6% of injected dispersed-signal fluence, and runs 6.2-7.0x faster than filtool in compute-only benchmarks.