Generative adversarial synthetic neighbors-based unsupervised anomaly detection
Abstract Anomaly detection is crucial for the stable operation of mechanical systems, securing financial transactions, and ensuring network security, among other critical areas. Presently, Generative Adversarial Networks (GANs)-based anomaly detection methods either require labeled data for semi-sup...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-84863-6 |
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