网络安全与数据治理2025，Vol.44Issue(12)：39-47,9.DOI:10.19358/j.issn.2097-1788.2025.12.006
融入注意力机制的改进YOLOv8 n低空飞行器检测技术
Research on low-altitude aircraft recognition technology based on YOLOv8n and attention mechanism
摘要
Abstract
This study addresses the challenge of detecting small low-altitude aircraft in complex environments,and proposes a vis-ual detection method based on an improved YOLOv8n model.The YOLOv8-SE model was constructed by integrating the light-weight AKConv convolution module,the SEAM channel-spatial mixed-domain attention module,and the repulsion loss function.A custom dataset was used for training and testing.The AKConv module enhances the flexibility of feature extraction by dynami-cally adjusting the sampling positions of convolution kernels,the SEAM module improves the ability to capture key features,and the repulsion loss function enhances detection accuracy in occluded environments.Experimental results demonstrate that YOLOv8-SE outperforms traditional models across multiple evaluation metrics.This research provides an efficient and reliable solution for small aerial targets detection and offers new insights into optimizing deep learning models for resource-constrained devices.关键词
小型低空飞行器/YOLOv8n/AKConv卷积/注意力机制Key words
small aerial targets/YOLOv8n/AKConv convolution/attention mechanism分类
信息技术与安全科学引用本文复制引用
Yang Guangfei,Zhang Leilei..融入注意力机制的改进YOLOv8 n低空飞行器检测技术[J].网络安全与数据治理,2025,44(12):39-47,9.基金项目
国家自然科学基金(42071273) （42071273）
中央高校基本科研业务费项目(DUT24YG147) （DUT24YG147）
