Image Classification on CIFAR-10 (test) (Accuracy Statistics)
92.82Best AccuracyIDE-LIF
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| IDE-LIFNetwork structure=CIFARNet-F, Time steps=100, Neurons=232K, Params=11.8M2021.09 | 92.82 | 92.52 | 0.17 | |
| ANN-SNNNetwork structure=VGG-16, Time steps=400-600, Neurons=318K, Params=40M2021.09 | 92.26 | — | — | |
| IDE-LIFNetwork structure=CIFARNet-F, Time steps=30, Neurons=232K, Params=11.8M2021.09 | 92.23 | 92.08 | 0.14 | |
| IDE-LIFNetwork structure=AlexNet-F, Time steps=100, Neurons=159K, Params=3.7M2021.09 | 92.15 | 92.03 | 0.07 | |
| IDE-LIFNetwork structure=AlexNet-F, Time steps=30, Neurons=159K, Params=3.7M2021.09 | 91.92 | 91.74 | 0.09 | |
| ANN-SNNNetwork structure=VGG-16, Time steps=2500, Neurons=311K, Params=15M2021.09 | 91.55 | — | — | |
| TSSL-BPNetwork structure=CIFARNet, Time steps=5, Neurons=726K, Params=45M2021.09 | 91.41 | — | — | |
| ASF-BPNetwork structure=VGG-7, Time steps=400, Neurons=>240K, Params=>30M2021.09 | 91.35 | — | — | |
| Hybrid TrainingNetwork structure=VGG-16, Time steps=100, Neurons=318K, Params=40M2021.09 | 91.13 | — | — | |
| ANN-SNNNetwork structure=CIFARNet, Time steps=400-600, Neurons=726K, Params=45M2021.09 | 90.61 | — | — | |
| STBPNetwork structure=CIFARNet, Time steps=12, Neurons=726K, Params=45M2021.09 | 90.53 | — | — | |
| Surrogate gradientNetwork structure=VGG-9, Time steps=100, Neurons=274K, Params=5.9M2021.09 | 90.45 | — | — | |
| TSSL-BPNetwork structure=AlexNet, Time steps=5, Neurons=595K, Params=21M2021.09 | 89.22 | 88.98 | 0.27 | |
| STBPNetwork structure=AlexNet, Time steps=12, Neurons=595K, Params=21M2021.09 | 85.24 | — | — |