Image Classification on ImageNet 1k (val) (Accuracy & T)
72.35AccuracyQCFS
Evaluation results
| Method | Links | ||
|---|---|---|---|
| QCFSModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 72.35 | 64 | |
| SEENN-IModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 71.84 | 29.53 | |
| CalibrationModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 71.12 | 64 | |
| SEENN-IModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 70.18 | 23.47 | |
| QCFSModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 69.37 | 32 | |
| TEBNModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 68.28 | 4 | |
| TETModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 68 | 4 | |
| SEENN-IModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 67.99 | 2.35 | |
| SEENN-IIModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 67.48 | 1.79 | |
| SEWModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 67.04 | 4 | |
| SEENN-IModel=SEW-ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 66.21 | 1.66 | |
| TETModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 64.79 | 6 | |
| SEENN-IModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 64.66 | 3.38 | |
| CalibrationModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 64.54 | 32 | |
| TEBNModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 64.29 | 6 | |
| SEENN-IIModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 64.18 | 2.4 | |
| tdBNModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 63.72 | 6 | |
| SEENN-IModel=ResNet-34, Training Paradigm=Direct Training of SNNs2023.04 | 63.65 | 2.28 | |
| OptModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 59.52 | 64 | |
| QCFSModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 59.35 | 16 | |
| OptModel=ResNet-34, Training Paradigm=ANN-SNN Conversion2023.04 | 33.01 | 32 |