【摘要】 针对家用燃气表人工集中抄表作业过程中检测背景复杂、实时性差、数字目标小等问题，提出了一种基于改进的YOLOX家用燃气表数字检测算法S-YOLOX。首先，削减CSPDarknet结构，降低主干网络的深度；其次，对特征金字塔进行调整，加强小目标物体检测；最后，修订PANet和Head结构的激活函数，解决梯度轻微爆炸问题。实验结果表明，SYOLOX算法不仅减少了模型的参数量，而且提高了检测精度，其中S-YOLOX-l模型平均精度（mAP）达到了94.9%，提高了2.2%，模型大小仅为原模型的32.9%。更多还原

【Abstract】 Aiming at the problems of complex detection background, poor real-time performance and small digital target in the process of manual centralized reading of household gas meter, a digital detection algorithm S-YOLOX based on improved YOLOX household gas meter is proposed. Firstly, reduce the structure of CSPDarknet and reduce the depth of backbone network; Secondly,the feature pyramid is adjusted to strengthen the detection of small target objects; Finally, the activation functions of PANet and Head structures are revised to solve the problem of gradient slight explosion. The experimental results show that S-YOLOX algorithm not only reduces the number of parameters of the model, but also improves the detection accuracy. Among them, the average accuracy(mAP) of S-YOLOX-l model is 94.9%, increased by 2.2%, and the size of the model is only 32.9% of the original model.更多还原