Anomaly Detection on Fatigue dataset (test)
99.62PrecisionCAE-M
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CAE-M2021.07 | 99.62 | 99.59 | 99.6 | |
| ConvLSTM-COMP2021.07 | 93.73 | 93.16 | 93.44 | |
| ConvLSTM-AE2021.07 | 90.1 | 93.46 | 91.75 | |
| UODA2021.07 | 82.8 | 77.7 | 80.17 | |
| MSCRED2021.07 | 80.16 | 68.02 | 73.59 | |
| LSTM-AE2021.07 | 71.4 | 68.2 | 68.7 | |
| ABOD2021.07 | 66.79 | 61.45 | 64.01 | |
| HMM2021.07 | 60.66 | 60.76 | 60.71 | |
| CNN-LSTM2021.07 | 57.8 | 50.42 | 53.86 | |
| OCSVM2021.07 | 56.05 | 57.1 | 52.9 | |
| KPCA2021.07 | 53.41 | 50.14 | 51.73 |