MIM-GAN-based Anomaly Detection for Multivariate Time Series Data-Reference-Cited by-同舟云学术

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MIM-GAN-based Anomaly Detection for Multivariate Time Series Data

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
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Author:

Lu Shan¹,Dong Zhicheng¹,Cai Donghong²,Fang Fang³,Zhao Dongcai¹

Affiliation:

1. Tibet University,College of Information Science Technology,Lhasa,China,850000

2. Jinan University,College of Information Science and Technology,Guangzhou,China,510632

3. Western University,Department of Electrical and Computer Engineering,London,Canada,N6A5B9

Funder

Research and Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10333258/10333344/10333517.pdf?arnumber=10333517

Reference18 articles.

1. Big Data Analytics for Event Detection in the IoT-Multicriteria Approach

2. Anomaly Detection in Cyber Physical Systems Using Recurrent Neural Networks

3. Switching Gaussian Mixture Variational RNN for Anomaly Detection of Diverse CDN Websites

4. Hyperspectral Anomaly Detection Based on Machine Learning: An Overview

5. Unsupervised Learning for Network Flow Based Anomaly Detection in the Era of Deep Learning

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multivariate Time-Series Anomaly Detection in IoT with a Bi-Dual GM GRU Autoencoder;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

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