Medical Image Classification on BreaKHis high-resolution
89.52AccuracyMH-pFLGB
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| MH-pFLGBModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 89.52 | 86.97 | |
| KT-pFLModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 84.24 | 81.33 | |
| pFedDFModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 82.33 | 79.41 | |
| FedRepModel Architecture=Unified (ResNet17)2024.06 | 79.91 | 76.18 | |
| LG-FedAvgModel Architecture=Unified (ResNet17)2024.06 | 79.72 | 75.23 | |
| Only Local TrainingModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 78.91 | 73.19 | |
| DS-PFLModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 78.42 | 76.09 | |
| FedProx+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 78.27 | 73.2 | |
| SCAFFOLD+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 77.61 | 72.29 | |
| FedAvg+FTModel Architecture=Unified (ResNet17), Fine-tuned=true2024.06 | 77.49 | 72.18 | |
| FedDFModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 76.61 | 72.53 | |
| FedMDModel Architecture=Heterogeneous (ResNet17, 11, 8, 5)2024.06 | 75.99 | 70.83 | |
| APFLModel Architecture=Unified (ResNet17)2024.06 | 74.44 | 65.68 | |
| SCAFFOLDModel Architecture=Unified (ResNet17)2024.06 | 74.42 | 65.12 | |
| FedAvgModel Architecture=Unified (ResNet17)2024.06 | 74.06 | 64.25 | |
| FedProxModel Architecture=Unified (ResNet17)2024.06 | 73.54 | 63.86 | |
| DittoModel Architecture=Unified (ResNet17)2024.06 | 73.04 | 62.21 |