Design of high automatic target recognition unmanned reconnaissance system based on YOLOv5

This essay analyzes the defects of target recognition in the field of unmanned reconnaissance, and gives an optimization strategy based on YOLOv5 algorithm. The feasibility of this system is verified by simulation experiment and real machine test, which has certain help to the battlefield unmanned reconnaissance. Then, the simulation experiment of unmanned reconnaissance system target detection and recognition was carried out, which mainly collected and established target data sets of armored vehicles, helicopters and people, and completed target recognition model training. After that, the parameters of the training results were analyzed, and the weights obtained from the training were tested. The algorithm was optimized and improved according to the characteristics of the uav targets in the ultra-low altitude perspective, and the model training and testing were carried out for many times, which improved the recognition rate of small and medium targets in the actual scene.