Unsupervised anomaly detection approach for time-series in multi-domains using deep reconstruction error
© 2020 by the authors. Automatic anomaly detection for time-series is critical in a variety of real-world domains such as fraud detection, fault diagnosis, and patient monitoring. Current anomaly detection methods detect the remarkably low proportion of the actual abnormalities correctly. Furthermor...
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| Main Authors: | , , , |
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| Format: | Journal |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85089546982&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70379 |
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| Institution: | Chiang Mai University |