Defect Detection On Dagm2007
Metrics
Average Accuracy
Results
Performance results of various models on this benchmark
Model Name | Average Accuracy | Paper Title | Repository |
|---|---|---|---|
| Auto-Classifier | 100 | Auto-Classifier: A Robust Defect Detector Based on an AutoML Head | - |
| Segmentation+Decision Net (end-to-end) | 100 | Mixed supervision for surface-defect detection: from weakly to fully supervised learning | - |
| Segmentation+Decision Net (end-to-end) | - | End-to-end training of a two-stage neural network for defect detection | - |
| CNN-Fusion | 99.9 | Auto-Classifier: A Robust Defect Detector Based on an AutoML Head | - |
| VGG-16 | 99.9 | Auto-Classifier: A Robust Defect Detector Based on an AutoML Head | - |
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