Medical Image Classification on BreaKHis downsampling eighth x8↓
77.93AccuracyMH-pFLGB
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| MH-pFLGBModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 77.93 | 72.14 | |
| KT-pFLModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 70.32 | 62.19 | |
| Only Local TrainingModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 69.56 | 58.67 | |
| pFedDFModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 68.43 | 60.22 | |
| FedDFModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 66.27 | 56.27 | |
| FedMDModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 64.95 | 54.39 | |
| FedRepModel Architecture=Unified (ResNet17)2024.06 | 63.28 | 50.91 | |
| DS-PFLModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 63.27 | 52.29 | |
| FedAvg+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 62.34 | 50.73 | |
| SCAFFOLD+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 61.42 | 50.05 | |
| APFLModel Architecture=Unified (ResNet17)2024.06 | 61.33 | 49.86 | |
| LG-FedAvgModel Architecture=Unified (ResNet17)2024.06 | 60.8 | 49.02 | |
| FedProx+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 60.71 | 48.29 | |
| DittoModel Architecture=Unified (ResNet17)2024.06 | 59.31 | 47.41 | |
| SCAFFOLDModel Architecture=Unified (ResNet17)2024.06 | 58.66 | 47.32 | |
| FedProxModel Architecture=Unified (ResNet17)2024.06 | 58.21 | 46.87 | |
| FedAvgModel Architecture=Unified (ResNet17)2024.06 | 57.74 | 46.81 |