A target detection method for underwater pipeline in side scan sonar images based on semantic segmentation
To improve the automation and efficiency of pipeline target detection in side scan sonar images,a underwater pipeline target detection method based on semantic segmentation is proposed.Firstly,the network computing speed is improved and the demand for computer hardware performance is reduced by building more efficient network backbone.Secondly,a weighted cross entropy loss function is proposed to solve the problem of network training difficulties caused by the imbalance of the number of classes according to the characteristics of pipeline targets.Underwater pipeline detection experiments were conducted using measured data under various complex conditions.The results showed that the proposed method achieved a speed increase of 2.7 times,reaching 52.6 FPS,and achieved fast and accurate detection of underwater pipelines with similar accuracy as classical networks.
万方数据
维普
