目标检测作为信息技术学界的热门话题, 无论是科研院校, 还是大型的技术型企业, 都在追寻着最优秀的目标检测算法, RetinaNet技术的提出者FacebookAI团队参考了大量目标检测的案例, 使其在目标检测领域成为炙手可热的方法, 它比YOLOv3更加优秀, 也没有Fastest R-CNN复杂, 十分适用于对指定特征目标的识别。就RetinaNet在军用车辆目标检测方面展开了研究, 并提出了一点改进意见。

In recent years, object detection has become a hot topic in the field of information technology.Whether it is a research institute or a large-scale technology-based enterprise, it is pursuing the best object detection algorithm.RetinaNet is an important discovery.It can be seen that the Facebook AI team, the proponent of RetinaNet, has referenced a large number of object detection cases, making it a hot method in the field of object detection.It is better than YOLOv3 and is not so complex as Fastest R-CNN.In this paper, the application of RetinaNet in military vehicle detection is studied, and some suggestions are put forward for improvement.