TSI-GAN: Unsupervised Time Series Anomaly Detection Using Convolutional Cycle-Consistent Generative Adversarial Networks

Shyam Sundar Saravanan; Tie Luo; Mao V. Ngo

doi:10.1007/978-3-031-33374-3_4

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TSI-GAN: Unsupervised Time Series Anomaly Detection Using Convolutional Cycle-Consistent Generative Adversarial Networks

Shyam Sundar Saravanan Tie Luo Mao V. Ngo

Year: 2023 Lecture notes in computer science Pages: 39-54 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-33374-3_4

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Keywords:

Computer science Anomaly detection Ground truth Key (lock) Artificial intelligence Intrusion detection system Time series Convolution (computer science) Data mining Pattern recognition (psychology) Machine learning Artificial neural network

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Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Digital Media Forensic Detection

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

TSI-GAN: Unsupervised Time Series Anomaly Detection Using Convolutional Cycle-Consistent Generative Adversarial Networks

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