Research on Cotton Mulch Recognition Method Based on Improved YOLOv5s Model
Aiming at the problem of difficult removal of plastic film impurities in the process of removing cotton impu-rities,a deep learning method was adopted for removal,and an improved YOLOv5s based plastic film recognition model was proposed.Firstly,the YOLOv5s model loss function was improved to improve the recognition accuracy of plastic film while ensuring the detection speed was met;Secondly,adding CA(Coordinate Attention)attention mechanism enhances the algorithm's feature extraction ability and detection accuracy,further improving the recogni-tion accuracy of cotton plastic film,and obtaining accurate location information of plastic film impurities.The experi-mental results show that compared to traditional methods,the use of deep learning can further identify 89.9％of plas-tic film impurities on the basis of original removal,effectively improving the quality of cotton;Compared with the original YOLOv5s model,the improved model achieved recognition accuracy and recall of 88.3％and 86.3％,re-spectively,with an increase of 7.5％and 7.9％.The detection effect of plastic film impurities was significantly im-proved,effectively solving the problem of difficult removal of plastic film impurities.
万方数据
维普
