Deep CNNs with spatial continuity preservation and a new weighted loss function outperform Random Forest in cross-regional transfer for satellite-derived bathymetry, achieving low RMSE on independent tests and a public benchmark.
Lyzenga, Shallow-water bathymetry using combined lidar and passive multispectral scanner data, Int
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From Local Training to Large-Scale Mapping: A Comparative Assessment of Machine Learning and Deep Learning for Transferable Satellite-Derived Bathymetry
Deep CNNs with spatial continuity preservation and a new weighted loss function outperform Random Forest in cross-regional transfer for satellite-derived bathymetry, achieving low RMSE on independent tests and a public benchmark.