A Novel FS-GAN-Based Anomaly Detection Approach for Smart Manufacturing
In this study, we present the few-shot generative adversarial network (FS-GAN) model, which integrates few-shot learning and a generative adversarial network with an unsupervised learning approach (AnoGAN) to address the challenges of anomaly detection in smart-factory manufacturing environments. Ma...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/13/1/21 |
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