Research on Tobacco Stem Recognition Algorithm Based on YOLOv4
In response to the problem of identifying and locating tobacco stems during tobacco loading and unloading in tobacco grading systems,this paper proposed a YOLOv4 convolutional neural network.Based on this,depth separable convolution was intro-duced,and the width factor alpha variable was introduced in depth separable convolution to optimize system parameters and simpli-fied network structure.The experimental results showed that the mAP value of the algorithm proposed in this paper was superior to several object detection algorithms such as SSD,Centernet,Faster-rcnn,YOLOv4little,and YOLOv4 in single pose tobacco stem rec-ognition.In multi pose tobacco stem recognition,the difference in mAP value between the algorithm and YOLOv4 algorithm is only 2%,but it can significantly reduce network parameters,improve model detection accuracy and system recognition speed.
tobacco stem recognition and localizationYOLOv4EfficientNetdepthwise separable convolution
NETL
NSTL
万方数据
维普
