A Comprehensive Real-World Photometric Stereo Dataset for Unsupervised Anomaly Detection
Unsupervised anomaly detection is a technology that trains a model to detect anomalies using only normal data. One of the main challenges of anomaly detection is detecting defects that are not visible or obscured by lighting conditions. However, most existing methods use a single image as an input t...
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| Hoofdauteurs: | , , , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
IEEE
2022-01-01
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| Reeks: | IEEE Access |
| Onderwerpen: | |
| Online toegang: | https://ieeexplore.ieee.org/document/9916256/ |
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