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Abstract Accurate building extraction from synthetic aperture radar (SAR) imagery is important for urban mapping, disaster assessment, and remote-sensing interpretation, but remains difficult because speckle noise, heterogeneous scattering, radar shadow, weak texture, and ambiguous building boundaries can degrade pixel-level predictions. At the same time, heavy segmentation networks are difficult to deploy in computation-constrained settings.
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