Image Classification on CIFAR-10 (test) (Baseline, Pruned, FR/PR Evaluation)
94.81Baseline AccuracyGAL-0.01
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| GAL-0.01Backbone=DenseNet-402026.01 | 94.81 | 94.29 | 52 | 35.13 | 35.58 | |
| HRankBackbone=DenseNet-402026.01 | 94.81 | 93.68 | 113 | 60.94 | 53.85 | |
| DCTBackbone=DenseNet-402026.01 | 94.81 | 94.32 | 49 | 38.5 | 40.4 | |
| Chen et al.Backbone=DenseNet-402026.01 | 94.22 | 93.56 | 66 | 44.4 | 60.08 | |
| Li et al.Backbone=DenseNet-402026.01 | 94.19 | 93 | 119 | 43.09 | 24.03 | |
| Zhao et al.Backbone=DenseNet-402026.01 | 94.11 | 93.16 | 95 | 44.78 | 59.67 | |
| SCAPBackbone=DenseNet-40, t=0.52026.01 | 93.72 | 92.53 | 119 | 75.92 | 77.87 | |
| SCAPBackbone=DenseNet-40, t=0.62026.01 | 93.72 | 91.51 | 221 | 84.1 | 86.46 |