A Partially Labeled Anomaly Data Detection Approach Based on Prioritized Deep Reinforcement Learning for Consumer Electronics Security

IF 4.3 2区计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Consumer Electronics Pub Date : 2024-08-19 DOI:10.1109/tce.2024.3445629

Shuqi Qin, Shenghao Liu, Shengjie Ye, Xiaoxuan Fan, Minmin Cheng, Yuanyuan He, Xianjun Deng, Jong Hyuk Park

引用次数: 0

查看原文本刊更多论文

基于优先级深度强化学习的部分标记异常数据检测方法，适用于消费电子产品安全

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Consumer Electronics 工程技术-电信学

CiteScore

7.70

自引率

9.30%

发文量

审稿时长

3.3 months

期刊介绍： The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.