期刊文献+

基于改进Mobilenet-V3的纽扣电池注塑盖缺陷检测识别

下载PDF
导出
摘要 工业纽扣电池在生产过程中,不可避免会出现不良品。为解决人工挑拣效率低、漏检率高、成本高的问题,提出一种基于改进Mobilenet-V3网络的纽扣电池注塑盖缺陷检测模型。首先以Mobilenet-V3作为注塑盖缺陷特征提取的主干网络,对主干网络进行轻量化修剪,并引入了CBAM注意力机制替代Mobilenet-V3网络原有的SE注意力机制模块,增强模型的表征能力。 In the production process of industrial button batteries,defective products will inevitably appear.In order to solve the problems of low efficiency,high omission rate and high cost of manual picking,a defect detection model of button battery cover based on improved Mobilenet-V3 network is proposed.Firstly,Mobilenet-V3 is used as the backbone network for defect feature extraction,and the backbone network is lightened and pruned,and CBAM attention mechanism is introduced to replace the SE attention mechanism module of Mobilenet-V3 network to enhance the representation ability of the model.
出处 《工业控制计算机》 2024年第11期42-44,共3页 Industrial Control Computer
关键词 神经网络 Mobilenet-V3 CBAM注意力机制 图像识别 neural network Mobilenet-V3 CBAM attention mechanism image identification
  • 相关文献

参考文献5

二级参考文献41

  • 1赵创,张为.基于HCORDIC的浮点运算协处理器的设计[J].电子测量与仪器学报,2020(11):58-65. 被引量:2
  • 2Boser B E, Guyon I M, Vapnik V N. A Training Algorithm for Opti- mal Margin Classifiers// Proc of the 5th Annual ACM Conference on Computational Learning Theory. Pittsburgh, USA, 1992: 144-152.
  • 3Suykens J A K, Van Gestel T, de Brabanter J, et al. Least Squares Support Vector Machines. Singapore: World Scientific, 2002.
  • 4Suykens J A K, Vandewalle J. Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 1999, 9(3 ) : 293- 300.
  • 5Lazaro J L, Dorronsoro J R. Least 1 -Norm SVMs: A New SVM Vari- ant between Standard and LS-SVMs// Proc of the 18th European Symposium on Artificial Neural Networks. Bruges, Belgium, 2010: 135-140.
  • 6Suykens J A K, de Brabanter J, Lukas L, et al. Weighted Least Squares Support Vector Machines: Robustness and Sparse Approxi- mation. Neurocomputing, 2002, 48( 1 ) : 85-105.
  • 7Valyon J, Horv~tth G. A Weighted Generalized LS-SVM. Periodica Polytechnica Electrical Engineering, 2003, 47 (3/4) : 229-251.
  • 8LESKI J M. Iteratively Reweighted Least Squares Classifier and Its l2-and l1 -Regularized Kernel Versions. Bulletin of The Pohsh Acad- emy of Sciences: Technical Sciences, 2010, 58( 1 ) : 171-182.
  • 9Liu Jingli, Li Jianping, Xu Weixuan, et al. A Weighted Lq Adap- tive Least Squares Support Vector Machine Classifiers-Robust and Sparse Approximation. Export Systems with Applications, 2011, 38 (3) : 2253-2259.
  • 10Chang K W, Hsieh C J, Lin C J. Coordinate Descent Method for Large-Scale lz-Loss Linear SVM. Journal of Machine Learning Research, 2008, 9:1369-1398.

共引文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部