A hybrid deep learning-based unsupervised anomaly detection in high dimensional data
Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data....
| Main Authors: | Muneer, A., Taib, S.M., Fati, S.M., Balogun, A.O., Aziz, I.A. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.28890 / |
| Published: |
Tech Science Press
2022
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117009228&doi=10.32604%2fcmc.2022.020732&partnerID=40&md5=0a89f42575a6dd3c06e57dbb05782837 http://eprints.utp.edu.my/28890/ |
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