【摘要】 梢斑螟是一种严重危害针叶树种的害虫，严重影响针叶树的健康和生长。梢斑螟虫的幼虫以针叶树的叶片为食物，在针叶树木中建立巢穴，逐渐摧毁叶片组织，导致叶片变黄、褪绿，最终树木枯萎。此外，幼虫也可能侵蚀树木的树皮，导致树皮剥落和树干暴露，使树木易受其他害虫、病菌和自然元素的侵害，增加树木的脆弱性，降低其生存能力。为辅助地面治疗被梢斑螟虫蛀树木，采用YOLOv8s目标检测算法，实现对梢斑螟虫蛀树木的检测与识别。通过采用C2f-GAM和动态检测头建立模型（YOLOv8-DM），来提高YOLOv8s对于梢斑螟虫蛀树木的检测能力。试验结果表明，YOLOv8-DM能够有效地识别梢斑螟虫蛀树木，其平均精准度达到84.8%。与其他目标检测算法相比，YOLOv8-DM有更高的平均精准度。更多还原

【Abstract】 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 C2fGAM 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.更多还原