Maturity detection of Euryale ferox seeds based on YOLOv8 modeling
An improved detection and sorting model based on YOLOv8 was proposed,improving the accuracy and efficiency in maturity sorting of Euryale ferox.Taking the Euryale ferox seeds as the object,preprocessing was made by the collected images of Euryale ferox seeds with coat skin,the SE module was introduced into the basic YOLOv8 model to improve the feature extraction capability,and WIoU function was used to further improve the model accuracy,and multiple model comparison tests were conducted.After the improvement,the average precision(P),recall(R)and mean average precision(mAP)reached 99.6％,99.8％,99.4％,respectively.Compared with the original YOLOv8 model,the accuracy was improved by 1.8％,1.6％,1.3％,respectively.A maturity detection model based on the improved YOLOv8 could identify and accurately classify the varieties of different maturity while maintaining light weight and high detection accuracy.
万方数据
维普
