2 papers
cs.CV2026
From Local Training to Large-Scale Mapping: A Comparative Assessment of Machine Learning and Deep Learning for Transferable Satellite-Derived Bathymetry
Hsiao-Jou Hsu, Joachim Moortgat
Satellite-derived bathymetry (SDB) from multispectral imagery is cost-effective but scales poorly across regions, especially in optically complex coastal environments. We evaluate…
cs.CV2026
From Bands to Depth: Understanding Bathymetry Decisions on Sentinel-2
Satyaki Roy Chowdhury, Aswathnarayan Radhakrishnan, Hsiao Jou Hsu +2
Deploying Sentinel-2 satellite derived bathymetry (SDB) robustly across sites remains challenging. We analyze a Swin-Transformer based U-Net model (Swin-BathyUNet) to understand ho…