Target detection algorithm based on deep learning needs high computer GPU configuration, even need to use high performance deep learning workstation, this not only makes the cost increase, also greatly limits the realizability of the ground, this paper introduces a kind of lightweight algorithm for target detection under the condition of the balance accuracy and computational efficiency, MobileNet as Backbone performs parameter The processing speed is 30fps on the RTX2060 card for images with the CNN separator layer. The processing speed is 30fps on the RTX2060 card for images with a resolution of 320*320.

翻译：基于深度学习的目标检测算法需要较高的计算机GPU配置，甚至需要使用高性能深度学习工作站，这不仅增加了成本，也极大限制了其在地面应用中的可实现性。本文介绍了一种平衡精度与计算效率的轻量级目标检测算法，采用MobileNet作为骨干网络（Backbone）进行参数处理。对于分辨率为320*320的图像，在配备CNN分离层的情况下，该算法在RTX2060显卡上的处理速度达到30fps。