The garbage classification and recognition algorithm is a hot topic in the current research.This paper optimi-zes the YOLOv3 algorithm by introducing the color block tracking module Lab color model,and uses the optimized algorithm to build a training model According to the current garbage category,we use web crawlers to crawl the common garbage ima-ges in daily life and classify them to form a data set Secondly,the optimized YOLOv3 algorithm is used to train the model of the processed data set,and the trained model is checked Finally,through practical testing,the average recognition accuracy of the optimized YOLOv3 algorithm reaches 94.33％.Compared with the original algorithm,the stability and accuracy of the optimized algorithm have been significantly improved.
维普
万方数据