Backbone | Method | Accuracy | # Params | GFLOPs |
ResNet-50 | [16] (baseline) (our reimplementation) | 94.93% | 23.7 | 3.8 |
ResNet-50 | MSTSM | 95.64% | 24.2 | 3.9 |
[16] + TFDEM | 95.71% | 23.9 | 3.9 | |
MSTSM + TFDEM | 96.25% | 24.5 | 4.0 | |
MSTSM + TFDEM + pruning | 95.57% | 22.4 | 3.6 | |
MSTSM-TFDEM-OF | 97.98% | 49.0 | 7.9 | |
EfficientNet-B0 | MSTSM | 95.60% | 4.23 | 0.7 |
MSTSM + TFDEM | 96.08% | 4.49 | 0.7 |