A Real-time UAV Object Detection System Design with FPGA Implementation

This paper proposes Target detection system design and FPGA implementation based on YOLOX algorithm, in order to realize offline real-time image detection in a UAV platform with limited resources and power consumption. First, this paper studied the algorithm of YOLOX convolutional neural network,image fusion mechanism is added to this network, designed and trained the neural network. Secondly, an embedded edge computing system is designed to further speed up the target detection speed at the hardware level.In this paper, the above scheme is implemented at the board level. The test results show that the average recognition speed is 50frame/s on the system, which basically achieves the design goal of real-time detection.