Research Article
Classification of Silicon (Si) Wafer Material Defects in Semiconductor Choosers using a Deep Learning ShuffleNet-v2-CNN Model
Table 3
Performance analysis of proposed ShuffleNet-v2-CNN model.
| Class | Accuracy | Precision | Recall | F1-Score |
| Center | 95.2 | 93.8 | 94.9 | 94.1 | Donut | 96.5 | 95.1 | 96.2 | 95.8 | Edge-Loc | 97.6 | 95.9 | 96.6 | 96.2 | Edge-Ring | 95.8 | 94.5 | 95.1 | 94.7 | Local | 96.5 | 93.8 | 95.8 | 95.0 | Near Full | 98.4 | 97.2 | 97.7 | 97.1 | Random | 97.0 | 96.1 | 96.3 | 95.9 | Scratch | 98.5 | 96.8 | 97.5 | 97.2 | Total Average | 96.93 | 95.4 | 96.26 | 95.75 |
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