The original YOLO V3 algorithm has low accuracy in small target detection and is prone to missed detection and false detection.To solve the problem,a ship target detection algorithm based on the improved YOLO V3 is proposed.Firstly,based on the structure of the original YOLO V3 network,an additional output scale is derived from the backbone network,whose feature information is spliced with that of the prior output scale,so as to obtain a feature vector with richer semantic information.Secondly,based on the data set,the clustering is improved,in which process the distance measurement formula is improved, and the number of anchor boxes and the corresponding parameters are reset.Finally,the loss function of the improved YOLO V3 is optimized,so as to improve the overall performance of the model.Analysis and experimental results on the test data set show that the average detection accuracy of the improved algorithm is 83.98%,which is 6.72% higher than that of the original YOLO V3.