测控技术2025，Vol.44Issue(3)：9-17,9.DOI:10.19708/j.ckjs.2025.03.303
基于改进YOLOv8的车辆与行人检测算法
Vehicle and Pedestrian Detection Algorithm Based on Improved YOLOv8
摘要
Abstract
Aiming at the problems of misdetection and omission of target objects,vehicles,and pedestrians ex-isting in the current mainstream target detection algorithm,an improved target detection algorithm based on YOLOv8 is proposed.Firstly,the multipoint distance intersection over union(MPDIoU)bounding box regression loss function is adopted to replace the original complete intersection over union(CIoU)loss function,effectively solving the problem that the traditional CIoU loss function will fails when the predicted bounding box has the same aspect ratio as the ground truth bounding box.Then,the multi-scale feature extraction capability of the al-gorithm is enhanced by embedding large separable kernel attention(LSKA)mechanism.Finally,the SCConv module is integrated to improve the target detection accuracy while reducing the computatational complexity of the model.The emperimental results show that compared with the original YOLOv8 algorithm,the improved al-gorithm has increased the precision by 4.07%,the recall by about 2.95%,and the detection rate reaches 85 f/s.关键词
目标检测/YOLOv8/注意力机制/MPDIoUKey words
target detection/YOLOv8/attention mechanism/MPDIoU分类
计算机与自动化引用本文复制引用
孙君峰,张赵良,刘云平,张涛,张诗云..基于改进YOLOv8的车辆与行人检测算法[J].测控技术,2025,44(3):9-17,9.基金项目
"太湖之光"科技攻关(基础研究)基金(K20221050) （基础研究）
无锡学院科研启动项目(550221034) （550221034）
