Research Article
MAM: Multiple Attention Mechanism Neural Networks for Cross-Age Face Recognition
Table 6
Rank-1 identification rates of the proposed MAM-CNN and other methods on MORPH dataset.
| Model | Rank-1 (%) |
| HFA [8] | 91.14 | CARC [20] | 92.80 | MEFA [10] | 93.80 | FaceNet [13] | 95.67 | LF-CNNs [16] | 97.51 | AE-CNNs [15] | 98.13 | ResNet-50(fine-tuned by MORPH) | 95.91 | Residual attention ResNet50 with HRC | 97.53 | Residual attention ResNet50 with HRC + self-attention | 98.84 | MAM-CNN | 99.07 |
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