This study presents SEAF-Net, a lightweight and efficient detection network designed for low-contrast and highly dynamic underwater environments. Built upon YOLOv11n, SEAF-Net introduces three complementary structural enhancements: (1) Omni-Dimensional Dynamic Convolution (ODConv) to improve adaptive modeling of multi-scale and directional texture variations; (2) SimA-SPPF, which embeds the SimAM attention mechanism into the S...

Shallow subsurface structure detection in coastal zones serves as a critical foundation for resource development and engineering construction. However, conventional geophysical methods exhibit significant limitations in land–sea transition zones, where pronounced “boundary effects” create substantial “exploration gaps” due to difficulties in merging terrestrial and marine datasets. To achieve truly seamless subsurface imaging...