Network Pruning On Cifar 10
Metrics
Accuracy
GFLOPs
Results
Performance results of various models on this benchmark
Model Name | Accuracy | GFLOPs | Paper Title | Repository |
|---|---|---|---|---|
| TAS-pruned ResNet-110 | 94.33 | 0.119 | Network Pruning via Transformable Architecture Search | - |
| MobileNet – Quantised | - | - | Quantisation and Pruning for Neural Network Compression and Regularisation | - |
| ShuffleNet – Quantised | - | - | Quantisation and Pruning for Neural Network Compression and Regularisation | - |
| AlexNet – Quantised | - | - | Quantisation and Pruning for Neural Network Compression and Regularisation | - |
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