Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis-Reference-Cited by-同舟云学术

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Case Study: A Semi-Supervised Methodology for Anomaly Detection and Diagnosis

Published:2019-12 Issue: Volume: Page:
ISSN:
Container-title:2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)
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Author:

Morales-Forero A.,Bassetto S.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8961317/8978490/08978509.pdf?arnumber=8978509

Cited by 12 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. quantile-Long Short Term Memory: A Robust, Time Series Anomaly Detection Method;IEEE Transactions on Artificial Intelligence;2024-08

2. AI-Assisted Identification of Primary and Secondary Metabolomic Markers for Post-Operative Delirium;2024-03-14

3. Bidirectional Backpropagation Autoencoding Networks for Image Compression and Denoising;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15

4. Acoustic Analysis of Cutting Tool Vibrations of Machines for Anomaly Detection and Predictive Maintenance;2023 IEEE 11th Region 10 Humanitarian Technology Conference (R10-HTC);2023-10-16

5. An interpretable semi‐supervised system for detecting cyberattacks using anomaly detection in industrial scenarios;IET Information Security;2023-05-09

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