Remote SAMsing pipeline boosts SAM2 coverage on remote sensing scenes from 30-68% to 91-98% via multi-pass masking and boundary-aware merging while preserving mask quality.
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SAM achieves ~58% accuracy delineating field boundaries from SkySat imagery without training, with gains from multi-date inputs and varied sizes, establishing proof-of-concept for data-scarce agriculture mapping.
citing papers explorer
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Remote SAMsing: From Segment Anything to Segment Everything
Remote SAMsing pipeline boosts SAM2 coverage on remote sensing scenes from 30-68% to 91-98% via multi-pass masking and boundary-aware merging while preserving mask quality.
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Investigating the Segment Anything Foundation Model for Mapping Smallholder Agriculture Field Boundaries Without Training Labels
SAM achieves ~58% accuracy delineating field boundaries from SkySat imagery without training, with gains from multi-date inputs and varied sizes, establishing proof-of-concept for data-scarce agriculture mapping.