High-quality semi-supervised anomaly detection with generative adversarial networks

Yuki Sato; Junya Sato; Noriyuki Tomiyama; Shoji Kido

doi:10.1007/s11548-023-03031-9

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High-quality semi-supervised anomaly detection with generative adversarial networks

Yuki Sato Junya Sato Noriyuki Tomiyama Shoji Kido

Year: 2023 Journal: International Journal of Computer Assisted Radiology and Surgery Vol: 19 (11)Pages: 2121-2131 Publisher: Springer Science+Business Media

DOI: 10.1007/s11548-023-03031-9

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Keywords:

Anomaly detection Visualization Discriminator Computer science Artificial intelligence Anomaly (physics) Pattern recognition (psychology) Abnormality Encoder Pixel Data mining

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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

Generative Adversarial Networks and Image Synthesis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

High-quality semi-supervised anomaly detection with generative adversarial networks

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Citation History

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