Image Classification on CIFAR-100 (test) (Accuracy and Timesteps)
69.27AccuracyOpt.
Evaluation results
| Method | Links | ||
|---|---|---|---|
| Opt.Model=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 69.27 | 64 | |
| Opt.Model=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 68.4 | 32 | |
| OPIModel=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 67.18 | 32 | |
| SEENN-IModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 65.48 | 6.19 | |
| Opt.Model=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 63.73 | 16 | |
| SEENN-IModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 56.99 | 4.41 | |
| QCFSModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 55.37 | 8 | |
| OPIModel=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 52.34 | 16 | |
| SEENN-IModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 39.33 | 2.57 | |
| QCFSModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 34.14 | 4 | |
| OPIModel=ResNet-20, Protocol=ANN-SNN conversion2023.04 | 23.09 | 8 | |
| QCFSModel=ResNet-18, Protocol=ANN-SNN conversion2023.04 | 19.96 | 2 |