黑龙江科技大学学报2024，Vol.34Issue(4)：642-647,6.DOI:10.3969/j.issn.2095-7262.2024.04.023
改进YOLOv8n的小目标检测算法
Small object detection algorithm based on improved YOLOv8n
赵金宪 1赵志滢1
作者信息
- 1. 黑龙江科技大学 计算机与信息工程学院,哈尔滨 150022
- 折叠
摘要
Abstract
This paper proposes a YOLOv8n_Y small object detection algorithm as a solusion to the is-sues of missed and false detections due to the inapparent target features in complex real scene.The study is accomplished by incorporating deformable convolution modules into the backbone network of the YOLOv8n model;adaptively adjusting the convolution kernel size by the deformable convolution module in situations with limited receptive fields in the target area to extract more feature information;adding CBAM attention mechanism to the Neck module,which has the attention mechanism focused on more im-portant object featur,as reducing the probability of false detections and improving the accuracy of small object detection.The results indicate that YOLOv8n_Y model achieves an improvement of the accuracy by 3.3%in the small target smoking dataset.关键词
YOLOv8n/可变形卷积模块/注意力机制/小目标检测Key words
YOLOv8n/deformable convolution module/attention mechanism/small object detec-tion分类
信息技术与安全科学引用本文复制引用
赵金宪,赵志滢..改进YOLOv8n的小目标检测算法[J].黑龙江科技大学学报,2024,34(4):642-647,6.
