Anomaly Detection on Robot-assisted feeding dataset
87.1AUCLSTM-VAE
Evaluation Results
| Method | Links | |
|---|---|---|
| LSTM-VAEInput=17 raw sensory signals2017.11 | 87.1 | |
| LSTM-VAEInput=4 hand-engineered features2017.11 | 85.64 | |
| AEInput=4 hand-engineered features2017.11 | 81.23 | |
| HMM-GPInput=4 hand-engineered features2017.11 | 81.21 | |
| EncDec-ADInput=17 raw sensory signals2017.11 | 80.75 | |
| AEInput=17 raw sensory signals2017.11 | 80.12 | |
| EncDec-ADInput=4 hand-engineered features2017.11 | 79.95 | |
| OSVMInput=4 hand-engineered features2017.11 | 74.27 | |
| OSVMInput=17 raw sensory signals2017.11 | 73.76 | |
| RandomInput=4 hand-engineered features2017.11 | 51.21 | |
| RandomInput=17 raw sensory signals2017.11 | 50.52 |