Time Series Anomaly Detection System with Linear Neural Network and Autoencoder-Reference-Cited by-同舟云学术

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Time Series Anomaly Detection System with Linear Neural Network and Autoencoder

Published:2023-03-17 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Device Intelligence, Computing and Communication Technologies, (DICCT)
language:
Short-container-title:

Author:

Mehra Pritika¹,Ahuja Mini Singh²,Aeri Manisha³

Affiliation:

1. Guru Nanak Dev University,Department of Computer Science,Amritsar,Punjab,India

2. GNDU Regional Campus,Department of Computer Science and Engineering,Gurdaspur,Punjab,India

3. Graphic Era Hill University,Department of Computer Science and Engineering,Dehradun,Uttrakhand,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10110034/10110036/10110220.pdf?arnumber=10110220

Reference34 articles.

1. A comprehensive survey of anomaly detection techniques for high dimensional big data

2. CTF: Anomaly Detection in High-Dimensional Time Series with Coarse-to-Fine Model Transfer

3. Unsupervised Anomaly Detection in Energy Time Series Data Using Variational Recurrent Autoencoders with Attention

4. A Comparison of Outlier Detection Techniques for High-Dimensional Data

5. Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

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. Federated Learning for Predictive Maintenance and Anomaly Detection Using Time Series Data Distribution Shifts in Manufacturing Processes;Sensors;2023-08-22

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