Table 2.
Classification performance for domain-adversarial neural networks (DANNs) with EfficientNetV2 backbone.
| Domain | Metric | Source-only | 1-shot DANN | 3-shot DANN | 5-shot DANN |
|---|---|---|---|---|---|
| BF source | Accuracy (%) | 94.4 | 91.1 | 94.4 | 93.3 |
| Precision (%) | 94.6 | 91.1 | 94.5 | 93.6 | |
| Recall (%) | 94.4 | 91.1 | 94.4 | 93.3 | |
| F1-score (%) | 94.4 | 91.0 | 94.4 | 93.3 | |
| BF target | Accuracy (%) | 41.7 | 56.7 | 75.0 | 73.3 |
| Precision (%) | 37.6 | 56.2 | 76.1 | 73.4 | |
| Recall (%) | 41.7 | 56.7 | 75.0 | 73.3 | |
| F1-score (%) | 38.2 | 53.4 | 73.1 | 73.3 | |
| 20 × source | Accuracy (%) | 94.4 | 90.0 | 90.0 | 93.3 |
| Precision (%) | 94.6 | 90.4 | 90.1 | 93.5 | |
| Recall (%) | 94.4 | 90.0 | 90.0 | 93.3 | |
| F1-score (%) | 94.4 | 90.0 | 89.9 | 93.4 | |
| 20 × target | Accuracy (%) | 33.3 | 54.4 | 82.2 | 88.9 |
| Precision (%) | 40.3 | 43.3 | 83.3 | 89.9 | |
| Recall (%) | 33.3 | 54.4 | 82.2 | 88.9 | |
| F1-score (%) | 28.1 | 46.8 | 82.0 | 88.8 | |
| 20x-5h source | Accuracy (%) | 94.4 | 94.4 | 94.4 | 94.4 |
| Precision (%) | 94.6 | 94.6 | 94.7 | 94.8 | |
| Recall (%) | 94.4 | 94.4 | 94.4 | 94.4 | |
| F1-score (%) | 94.4 | 94.4 | 94.5 | 94.5 | |
| 20x-5h target | Accuracy (%) | 40.0 | 71.7 | 83.3 | 83.3 |
| Precision (%) | 43.4 | 80.1 | 84.1 | 84.1 | |
| Recall (%) | 40.0 | 71.7 | 83.3 | 83.3 | |
| F1-score (%) | 34.1 | 70.9 | 81.3 | 81.3 |
Results are presented for source-only training and domain-adversarial training with 1-shot, 3-shot, and 5-shot labeled samples. Bold values indicate the highest accuracy for each domain and setting.