Image Classification on ImageNet-1K (test) (Accuracy & FLOPs)
74AccuracyPruneFuse
Evaluation results
| Method | Links | ||
|---|---|---|---|
| PruneFuseBudget (b)=50%, Params=4.59 M, Pruning ratio (p)=0.6, Backbone=ResNet-50, Sampling Strategy=Least-Confidence2026.03 | 74 | 54.88 | |
| PruneFuseBudget (b)=50%, Params=6.91 M, Pruning ratio (p)=0.5, Backbone=ResNet-50, Sampling Strategy=Least-Confidence2026.03 | 73.86 | 82.62 | |
| PruneFuseBudget (b)=50%, Params=2.74 M, Pruning ratio (p)=0.7, Backbone=ResNet-50, Sampling Strategy=Least-Confidence2026.03 | 73.84 | 32.76 | |
| PruneFuseBudget (b)=50%, Params=1.35 M, Pruning ratio (p)=0.8, Backbone=ResNet-50, Sampling Strategy=Least-Confidence2026.03 | 73.64 | 16.14 | |
| Baseline (AL)Budget (b)=50%, Params=25.5 M, Backbone=ResNet-50, Sampling Strategy=Least-Confidence2026.03 | 73.56 | 305.6 |