In recent years, owing to the rapid advancements in deep learning, advanced object detection methods, such as You Only Look Once (YOLO) and Efficient Detector (EfficientDet), have been frequently used to detect underwater organisms. However, due to the complexity of underwater scenarios and deployment limitations, these models often encounter various challenges, such as blurred targets, occlusions, and high model computing costs. On this basis, we propose a YOLO network (CGC-YOLO) based on Cross-Stage Partial Convolutional Block Attention Modul...
