The recognition and segmentation of seafloor topography play a crucial role in marine science research and engineering applications. However, traditional methods for seafloor topography recognition and segmentation face several issues, such as poor capability in analyzing complex terrains and limited generalization ability. To address these challenges, this study introduces the SG-MKD dataset (Submarine Geomorphology Dataset—S...

The utilization of synthetic aperture radar (SAR) for depth inversion is crucial for accurate underwater mapping. However, current SAR-based techniques face challenges in segmentation accuracy, which directly affects inversion precision and spatial resolution. Traditional segmentation methods lack efficiency and often result in low-resolution outcomes. To address these issues, we propose a novel SAR water depth inversion metho...

Outlier detection is the key to the quality control of marine survey data. For the detection of outliers in Conductivity-Temperature-Depth (CTD) data, previous methods, such as the Wild Edit method and the Median Filter Combined with Maximum Deviation method, mostly set a threshold based on statistics. Values greater than the threshold are treated as outliers, but there is no clear specification for the selection of threshold,...