Connection Recognition Method Using Improved YoloV4 Algorithm
In order to realize the automatic assembly and sorting of connectors,this paper proposes an improved YoloV4 algorithm for connector identification.First,CSP-Darknet53,the backbone network in YoloV4is replacedby a lightweight GhostNet network.At the same time,the ordinary convolution used in YoloV4is also replaced with a deeply separable convolution to further reduce the number of parameters,and K-means++clustering algorithm is used to avoid the shortcomings of K-means clustering algorithm and generate a priori box size.The experimental results show that the average accuracy of the improved YoloV4 algorithm is as high as 100％,the recognition speed is greatly improved,and the number of parameters is reduced by 82％compared with YoloV4,which can improve the application range of embedded devices and provide technical support for intelligent manufacturing.
国家科技期刊平台
NSTL
万方数据
