• Corpus ID: 235694261

One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map

@article{Yasuno2021OneclassSD,
  title={One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map},
  author={Takato Yasuno and Junichiro Fujii and Sakura Fukami},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.00143}
}
For steel product manufacturing in indoor factories, steel defect detection is important for quality control. For example, a steel sheet is extremely delicate, and must be accurately inspected. However, to maintain the painted steel parts of the infrastructure around a severe outdoor environment, corrosion detection is critical for predictive maintenance. In this paper, we propose a general-purpose application for steel anomaly detection that consists of the following four components. The first… 

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