Research on Civil Ship Image Classification Method Based on YOLOv8
The research on civilian ship image classification methods based on YOLOv8 continues to improve the level of shipping.The types of ships are gradually refined,and in the face of different uses of ships,accurate understanding of ship types provides conditions for people to better manage ships.This paper selects the FGSCR dataset.Eight types of crane ships,superyacht,cargo ships,container ships,tugs,small yachts,sand carriers and oil tankers are selected.Imple-ment civil ship image classification based on YOLOv8.Train the 5 models of YOLOv8,YOLOv8n,YOLOv8s,YOLOv8m,YOLOv8l,and YOLOv8x.The training results show that the model size has increased from 2.83 MB to 107MB,with YOLOv8m having the highest Top1 accuracy,reaching 96.97%.The deep learning method can be used to identify ship types in remote sensing data.
万方数据
维普
