现代信息科技2026，Vol.10Issue(10)：61-65,5.DOI:10.19850/j.cnki.2096-4706.2026.10.011
基于YOLO与动态正交注意力的暴力行为检测算法
Violence Detection Algorithm Based on YOLO and Dynamic Orthogonal Attention Mechanism
摘要
Abstract
Aiming at the problems of inadequate spatio-temporal information modeling and poor robustness in complex scenes in existing violence detection methods based on Deep Learning,a violence detection algorithm based on YOLO and hybrid Attention Mechanism is proposed.The algorithm integrates orthogonal channel attention OrthoNets into the C2f module in YOLO backbone network,and uses randomly initialized orthogonal filters to compress feature space information,ensuring feature diversity for subsequent extraction.The channel space mixed attention module CBAM is integrated into the Neck end to enhance the network feature representation capability.The experimental results demonstrate that the algorithm achieves accuracy,recall,and average precision of 91.25%,95.6%,and 87.5%,respectively,on the RWF-2000 dataset characterized by diverse content and complex environments.It outperforms the most advanced algorithms of the same kind at present in both accuracy metrics and robustness,fully validating its effectiveness.关键词
深度学习/暴力行为检测/YOLO/注意力机制Key words
Deep Learning/violence detection/YOLO/Attention Mechanism分类
信息技术与安全科学引用本文复制引用
吴家明,林可,冯楠,仇思思,文勇..基于YOLO与动态正交注意力的暴力行为检测算法[J].现代信息科技,2026,10(10):61-65,5.基金项目
广西民族大学自治区级大学生创新创业训练计划项目(S202310608294) （S202310608294）
广西民族大学研究生教育创新项目(gxmzu-chxs2024302) （gxmzu-chxs2024302）
