Research Article
[Retracted] Coupled Attention Framework of Convolutional Neural Network Based on Computer Intelligence
Table 1
Accuracy of ResNet methods on Cifar100.
| Method | Acc (%) | Params (M) | FLOPs (G) |
| ResNet18 | 77.86 | 11.22 | 0.56 | SE | 78.11 | 11.31 | 0.56 | CAF-SE | 79.00 | 11.31 | 0.56 | CBAM | 77.94 | 11.31 | 0.56 | CAF-CBAM | 78.25 | 11.31 | 0.56 | SGE | 76.67 | 11.23 | 0.56 | CAF-SGE | 77.17 | 11.23 | 0.56 |
| ResNet50 | 77.86 | 23.71 | 1.31 | SE | 80.18 | 26.26 | 1.32 | CAF-SE | 80.81 | 23.89 | 1.32 | CBAM | 80.12 | 26.26 | 1.33 | CAF-CBAM | 80.63 | 24.06 | 1.32 | SGE | 80.59 | 23.73 | 1.32 | CAF-SGE | 80.73 | 23.73 | 1.32 |
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