Hard Anomaly Detection: An Adversarial Data Augmentation Solution-Reference-Cited by-同舟云学术

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Hard Anomaly Detection: An Adversarial Data Augmentation Solution

Published:2023-12-04 Issue: Volume:abs/1802.06222 Page:1065-1075
ISSN:
Container-title:2023 IEEE International Conference on Data Mining Workshops (ICDMW)
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Author:

Teng Hu¹,Wang Cheng¹,Yang Qing¹,Chen Xue¹

Affiliation:

1. Tongji University,Department of Computer Science and Technology,Shanghai,China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Ministry of Education

Program of Shanghai Academic Research Leader

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411624.pdf?arnumber=10411624

Reference37 articles.

1. The Behavioral Sign of Account Theft: Realizing Online Payment Fraud Alert

2. Neural memory plasticity for medical anomaly detection

3. Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection

4. Robust unsupervised anomaly detection via multi-time scale DCGANs with forgetting mechanism for industrial multivariate time series

5. Gryphon: a semi-supervised anomaly detection system based on one-class evolving spiking neural network

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