Table 8.
Comparative experiments on gender recognition using Adience, LFW and FERET data-sets.
| Database | Method | Classification Accuracy (%) |
|---|---|---|
| Adience | RAG-MCFP-DCNNs | 93.6 |
| Levi et al. [91] | 86.8 | |
| Lapuschkin et al. [92] | 85.9 | |
| CNNs-EML [73] | 77.8 | |
| Hassner et al. [89] | 79.3 | |
| LFW | Van et al. [93] | 94.4 |
| RAG-MCFP-DCNNs | 94.1 | |
| HyperFace [94] | 94.0 | |
| LNets+ANet [95] | 94.0 | |
| Moeini et al. [96] | 93.6 | |
| PANDA-1 [47] | 92.0 | |
| ANet [56] | 91.0 | |
| Rai and Khanna [97] | 89.1 | |
| FERET | RAG-MCFP-DCNNs | 100 |
| Moeini et al. [96] | 99.5 | |
| Tapia and Perez [98] | 99.1 | |
| Rai and Khanna [97] | 98.4 | |
| Afifi and Abdelrahman [99] | 99.4 | |
| A priori-driven PCA [100] | 84.0 |