首页|基于改进YOLOv5网络的轮胎规格字符识别

基于改进YOLOv5网络的轮胎规格字符识别

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针对于汽车轮胎规格字符识别效率低、准确率低等问题,提出一种改进YOLOv5 网络的轮胎规格字符识别方法.首先,将YOLOv5 中的耦合头改为解耦头,提高网络的泛化能力;其次,提出C3-Faster模块,替换YOLOv5 的Backbone和Head中的部分C3 模块,提高网络的计算速度;最后,选用WIoU损失函数替换YOLOv5 的CIoU损失函数,优化网络.通过对比实验,验证了C3-Faster和WIoU损失函数的有效性,在消融实验中,改进后的网络训练时间减少,mAP提高了3.7%,Preci-sion提升2.1%.实验结果表明,该方法在汽车轮胎规格字符识别的有效性,提高了识别的准确性.
Improving Tire Specification Character Recognition in YOLOv5 Network
A method for improving the recognition of characters indicating specifications for automobile tires is proposed to address the issues of low efficiency and accuracy in character recognition.This method involves improving the YOLOv5 network by replacing the coupled head with a decoupled head to enhance the network's generalization ability.Additionally,a C3-Faster module is proposed to replace some C3 mod-ules in the YOLOv5 backbone and head,thereby increasing the network's computational speed.Finally,the WIoU loss function is selected to replace the CIoU loss function in YOLOv5 to optimize the network.Com-parative experiments have been conducted to verify the effectiveness of the C3-Faster and WIoU loss func-tion.The improved network reduced training time and increased mAP by 3.7%and precision by 2.1%in ablative experiments.The experimental results show that this method is effective in recognizing characters indicating specifications for automobile tires,improving recognition accuracy.

YOLOv5decoupling headC3-FasterWIoUtire specification character recognition

赵庆、魏鸿磊、杨祎宁、黄萌

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大连工业大学机械工程与自动化学院,大连 116034

YOLOv5 解耦头 C3-Faster WIoU 轮胎规格字符识别

辽宁省教育厅2021年度科学研究经费面上项目辽宁省教育厅2021年度科学研究经费面上项目2021年度本科教育教学综合改革项目2021年度本科教育教学综合改革项目

LJKZ0535LJKZ0526JGLX2021020JCLX2021008

2024

10.13462/j.cnki.mmtamt.2024.02.034

组合机床与自动化加工技术
大连组合机床研究所 中国机械工程学会生产工程分会

组合机床与自动化加工技术

CSTPCD北大核心
影响因子：0.671
ISSN：1001-2265
年,卷(期)：2024.(2)
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