基于YOLOv8算法改进模型检测梢斑螟虫蛀树木OA北大核心

Dioryctria is a kind of pest that seriously harms conifer species and seriously affects the health and growth of conifer trees.The larvae of Dioryctria feed on the leaves of coniferous trees and build nests in coniferous trees.Gradually,they destroy the leaf tissues,causing the needles to turn yellow and eventually leading to the withering of the trees.In addition,larvae may also erode the bark of trees,resulting in bark flaking and trunk exposure,leaving trees vulnerable to other pests,germs and natural elements,in-creasing the vulnerability of trees and reducing their viability.In order to assist the ground treatment of trees eaten by Dioryctria,the YOLOv8s target detection algorithm was adopted to realize the detection and recognition of the trees eaten by Dioryctria.By using C2f-GAM and dynamic detection head to build a model(YOLOv8-DM),the detection ability of YOLOv8s against Dioryctria moth trees was improved.The experimental results showed that YOLOv8-DM could effectively identify Dioryctria moth trees with an average accu-racy of 84.8%.Compared with other target detection algorithms,YOLOv8-DM has higher average precision.