Image Classification on ImageNette 1.0 (test)
90Accuracy (alpha=0.1)Central
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CentralModel Architecture=ResNet-182024.12 | 90 | 90 | 90 | |
| CentralModel Architecture=ConvNet2024.12 | 89.6 | 89.6 | 89.6 | |
| FedSD2CModel Architecture=ConvNet2024.12 | 50.68 | 57.89 | 58.17 | |
| FedSD2CModel Architecture=ResNet-182024.12 | 47.52 | 53.69 | 55.9 | |
| F-DAFLModel Architecture=ConvNet2024.12 | 44.95 | 52.23 | 58.34 | |
| DENSEModel Architecture=ConvNet2024.12 | 42.09 | 48.64 | 54.74 | |
| Co-BoostingModel Architecture=ConvNet2024.12 | 39.36 | 56.15 | 58.6 | |
| DENSEModel Architecture=ResNet-182024.12 | 38.37 | 47.85 | 49.78 | |
| F-DAFLModel Architecture=ResNet-182024.12 | 37.86 | 39.52 | 46.06 | |
| Co-BoostingModel Architecture=ResNet-182024.12 | 27.06 | 28.53 | 30.53 | |
| FedAVGModel Architecture=ConvNet2024.12 | 10.68 | 10.04 | 9.83 | |
| FedAVGModel Architecture=ResNet-182024.12 | 9.86 | 10.06 | 10.76 |