Underwater Sonar Target Detection Based on YOLOv5

Abstract

Sonar is widely used in seabed resources and military exploration. However, underwater sonar target detection methods are few and most of them are traditional algorithms. To solve this problem, an improved detection network based on YOLOV5 is designed in this paper. The model training and test results show that the model has a good ability to detect underwater sonar objects.