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Anomaly detection‐based intelligent computing in internet of things and network applications

  • Published:2021-05 Issue:3 Volume:4 Page:
  • ISSN:2476-1508
  • Container-title:Internet Technology Letters
  • language:en
  • Short-container-title:Internet Technology Letters

Author:

Zhu Fa1,Shankaran Rajan2,Zhao Bin3,Zhao Yongbin4,Gang Yining4,Chen Xingchi5

Affiliation:

1. Nanjing Forestry University Nanjing China

2. Macquarie University Sydney New South Wales Australia

3. Nanjing Normal University Nanjing China

4. Liaoning Electric Power Energy Development Group Co., Ltd Shenyang China

5. University of Technology Sydney Sydney New South Wales Australia

Publisher

Wiley

Subject

General Medicine

Reference9 articles.

1. A comprehensive survey on internet of things (IoT) toward 5G wireless systems;Chettri L;IEEE Internet Things J,2020

2. A survey of machine and deep learning methods for internet of things (IoT) security;Al‐garadi M;IEEE Commun Surv Tutor,2020

3. Unsupervised anomaly detection in IoT systems for smart cities;Guo Y;IEEE Trans Netw Sci Eng,2020

4. LSTM learning with Bayesian and Gaussian processing for anomaly detection in industrial IoT;Wu D;IEEE Trans Ind Inform,2020

5. RaghavendraChalapathyandSanjayChawla Deep Learning for Anomaly Detection: A Survey (2019) arXiv preprint arXiv:1901.03407.

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1. Research on Intelligent Patrol System for Wind Power Station;Proceedings of the 2024 3rd International Symposium on Robotics, Artificial Intelligence and Information Engineering;2024-07-05

2. Research and Application of Lane Intelligent Detection System Based on Internet of Things Technology;Lecture Notes in Electrical Engineering;2024

3. Deep dynamic face capture and recognition based on internet of things;Internet Technology Letters;2023-10-19

4. Wearable Device-Based Intelligent Patrol Inspection System Design and Implementation;International Journal of Distributed Systems and Technologies;2023-02-10

5. Abnormality Detection and Localization Schemes Using Molecular Communication Systems: A Survey;IEEE Access;2023
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