图像识别技术在广播电视节目内容监播中的应用  

Application of Image Recognition Technology in the Content Monitoring of Radio and Television Programs

作　　者：李际 LI Ji(Donggang Integrated Media Center,Donggang 118313,China)

机构地区：[1]东港市融媒体中心,辽宁东港118313

出　　处：《电视技术》2025年第2期168-170,共3页Video Engineering

摘　　要：图像识别技术广泛采用了卷积神经网络(Convolutional Neural Networks,CNN)、ResNet101、Faster R-CNN等深度学习模型,在违规内容检测、广告插播管理、节目质量控制等领域发挥着重要作用。XGBoost等分类算法作为辅助工具,进一步提升了内容分类的精度和效率。基于此,分析图像识别技术在广播电视节目内容监播中的具体应用。Image recognition technology widely adopts deep learning models such as Convolutional Neural Networks(CNN),ResNet101,Faster R-CNN,etc.,which play an important role in areas such as violation content detection,advertising insertion management,and program quality control.XGBoost and other classification algorithms,as auxiliary tools,further improve the accuracy and efficiency of content classification.Based on this,this paper analyzes the specific application of image recognition technology in the content monitoring of radio and television programs.

关 键 词：广播电视 节目内容监播 图像识别技术 

分 类 号：TN948.1[电子电信—信号与信息处理]