Research Article
A Machine Vision Anomaly Detection System to Industry 4.0 Based on Variational Fuzzy Autoencoder
Table 1
Performance evaluation of the proposed algorithm.
| ā | Precision | Recall | F-measure | Anomaly score |
| VFA_Instance_1 | 88.9 | 89.0 | 89.0 | 0.12 | VFA_Instance_2 | 86.7 | 87.1 | 86.8 | 0.18 | VFA_Instance_3 | 92.1 | 92.0 | 92.1 | 0.08 | VFA_Instance_4 | 89.9 | 89.9 | 89.9 | 0.11 | VFA_Instance_5 | 90.3 | 90.2 | 90.2 | 0.10 | VFA_Instance_6 | 84.5 | 84.7 | 84.8 | 0.22 | VFA_Instance_7 | 88.3 | 88.3 | 88.2 | 0.13 | VFA_Instance_8 | 94.2 | 94.2 | 94.0 | 0.06 | VFA_Instance_9 | 95.1 | 95.0 | 95.1 | 0.05 | VFA_Instance_10 | 93.4 | 93.4 | 93.4 | 0.06 | Average score | 90.34 | 90.38 | 90.35 | 0.11 |
|
|