Reservoir-enhanced segment anything model for subsurface diagnosis.

ABSTRACT: Urban roads and infrastructure, vital to city operations, face growing threats from subsurface anomalies like cracks and cavities. Ground Penetrating Radar effectively visualizes underground conditions using electromagnetic waves; however, accurate anomaly detection through this method remains challenging due to limited labeled data, varying subsurface conditions, and indistinct target boundaries. Although visually image-like, radar cross-sectional data fundamentally represent electromagnetic waves, with variations within and between waves critical for identifying anomalies. Addressing these, we propose the Reservoir-enhanced Segment Anything Model, a framework exploiting both visual discernibility and wave-changing properties of radar data. The model initially identifies visually apparent

SUBMITTER: Zhou X 

PROVIDER: S-EPMC12701067 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature