Research on ship detection of optical remote sensing image based on Yolo V5

Abstract

Abstract In order to achieve ship target detection based on remote sensing images in complex backgrounds, this paper proposes a ship target detection algorithm based on YOLO V5. First, the improved Kmeans is used to cluster the data set, DIOU_loss is used for the candidate frame selection strategy, and finally the channel attention mechanism is introduced. The experimental results show that under the same conditions, the improved network has a slight decrease in detection speed compared with the original YOLOv5 network, and the effect of images with densely distributed small targets is significantly improved. On the same test set, the accuracy rate is reduced by 3.84%, the recall rate is increased by 32.73%, and mAP is increased by 22.48%.