To solve the problem of low efficiency and large size of YOLOXs pedestrian target recognition algo-rithm.A lightweight convolutional neural network is used to replace the backbone network,and the 3×3 con-volutional layer in the feature enhancement network is replaced by a lightweight convolutional neural network.The results show that the lightweight enhanced network model can effectively reduce the number of parameters and memory on the basis of ensuring the accuracy of pedestrian target recognition.The parameters are reduced by 44.1％and the memory is reduced by 41.9％.This is more suitable for the construction of embedded and mobile devices,and has certain reference value for the development of intelligent vehicles.
维普
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