With the continuous development of computer vision, it becomes more and more important to make intelligent decisions through pure visual perception. Recently, deep reinforcement learning algorithms have been exploited to give intelligence to visual perception decision making. This paper mainly studies the application of deep learning in intelligent navigation. In this paper, YOLOv3 deep learning model is built and improved, the model is clipped, the deep learning model is lightweight, and the recognition speed is improved without significantly reducing the accuracy. Through the application and verification of the algorithm on the vehicle experimental platform, the real-time target tracking and autonomous navigation of the vehicle platform are realized.

Yonghu Hua. Deep Learning in Intelligent Navigation. International Journal of Neural Network (2020), Vol. 1, Issue 3: 18-25. https://doi.org/10.38007/NN.2020.010303.

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