青岛大学学报（自然科学版）2026，Vol.39Issue(2)：23-30,68,9.DOI:10.3969/j.issn.1006-1037.2026.02.04
基于改进YOLOv8的烟丝检测的实例分割算法
Instance Segmentation Algorithm for Tobacco Detection Based on Improved YOLOv8
王琨 1王恒澳 1刁瑞新 1计晓斐1
作者信息
- 1. 青岛大学计算机科学技术学院,青岛 266071
- 折叠
摘要
Abstract
Aiming at the problems of difficult segmentation of slender tobacco shreds,blurred edges and low detection efficiency,a lightweight instance segmentation algorithm based on the improved YOLOv8-EffDS-YOLO was proposed.The lightweight network EfficientNet-B2 was introduced as the backbone network in EHDS-YOLO.Combined with the long strip-shaped feature of tobacco shreds,a feature fusion module including dynamic serpentine convolution and convolutional block attention module was designed to improve the adaptability and response speed of the algorithm to tobacco shreds of different scales.Meanwhile,an edge-weighted loss function was adopted to improve the accuracy of edge segmentation.The experimental results show that,compared with the original YOLOv8 instance segmentation algorithm and other comparison methods,the improved algorithm has significant improvements in both recall rate and mAP@0.5 index,and the processing speed also meets the actual production requirements.关键词
实例分割/YOLOv8分割算法/轻量级网络/注意力机制/动态蛇形卷积Key words
instance segmentation/YOLOv8-segment/lightweight network/attention mechanism/dynamic serpentine convolution分类
信息技术与安全科学引用本文复制引用
王琨,王恒澳,刁瑞新,计晓斐..基于改进YOLOv8的烟丝检测的实例分割算法[J].青岛大学学报（自然科学版）,2026,39(2):23-30,68,9.
