福建电脑2024，Vol.40Issue(4)：35-39,5.DOI:10.16707/j.cnki.fjpc.2024.04.008
结合残差网络和TSM的暴力行为检测方法
A Violence Behavior Detection Method Combining Residual Networks and TSM
摘要
Abstract
Deep learning methods are commonly used to assist in detecting violent behavior,thereby reducing the dependence on manual intervention in surveillance videos.However,with the development of deep networks,problems such as vanishing gradients and overfitting have become more prominent.To address these issues,this paper proposes a method that combines residual networks and time transfer modules to fully explore the spatiotemporal information in frequency sequences,optimize action recognition performance,and improve the accuracy of violent behavior detection.The experimental results show that compared to directly using residual networks ResNet50 and ResNet101,our method improves the recognition accuracy of violent behavior by 1.4%and 0.7%,respectively.关键词
深度学习/暴力行为检测/残差网络Key words
Deep Learning/Violence Behavior Detection/Residual Networks分类
信息技术与安全科学引用本文复制引用
徐欣欣..结合残差网络和TSM的暴力行为检测方法[J].福建电脑,2024,40(4):35-39,5.基金项目
本文得到浙江工贸职业技术学院教师科技创新项目(理工类)(No.G220103)、温州市基础性科研项目(No.S20220041)资助. （理工类）
