Machine Learning-Driven Lateral Density Variation for High-Precision Bathymetry: Central-Northern South China Sea
By coupling neural network-derived density modelling with physically rigorous inversion, the approach overcomes limitations of uniform-density assumptions while retaining interpretability, providing an efficient and reliable approach to high-precision seafloor mapping in geologically complex regions.