UAV Tracking Algorithm Based on Attention Mechanism Improved Siamese Network
To cope with the problem of safety hazards caused by non-cooperative unmanned aerial ve-hicles(UAVs)and realize adequate supervision,a UAV target tracking algorithm based on improved siamese network is proposed.Firstly,the structure of the full-convolution siamese network(Siam-FC)is improved.Ghost convolution and integrated convolution block attention models are added to the network structure.Then,using the constructed UAV dataset,the improved network algorithm and three traditional target tracking algorithms named SiamFC,DeepSORT and FlowTrack are trained and verified.Finally,the four algorithms are compared and analyzed.The results show that the algorithm has an accuracy of 91.4%,a success rate of 69.6%,and better performance than the other three algorithms.Therefore,it can effectively track UAV targets.
万方数据
维普
