Drug Appearance Recognition Based on Object Detection
OBJECTIVE In the process of drug dispensing,using computer vision technology to identify drugs is vulnerable to the influence of lighting,angle,packaging and other factors,which will produce large identification errors.Therefore,this paper proposes an object detection algorithm for drug appearance recognition(YOLOv4-GhostNet-CMB).METHODS Firstly,the algorithm redesigned the backbone feature extraction network in YOLOv4 by using GhostNet.Secondly,the CA attention model was brought into the Ghost module,aggregate features along horizontal and vertical directions to enhance the precise positioning of drugs.Finally,Bi-FPN feature pyramid structure was introduced to connect with the new backbone,and added a feature graph output which could enhance feature extraction and improved the detection accuracy of drugs.RESULTS The experimental results show that the average detection accuracy of YOLOv4-GhostNet-CMB algorithm reached 92.24％,which was a significant improvement of 4.49％compared with YOLOv4 algorithm in term of detection accuracy.CONCLUSION The model size is only 150 MB,nd this algorithm can effectively identify drugs.
万方数据
维普
