|
| Ref. no. | Algorithm | Accuracy | Dataset |
|
| [53] | Principal component analysis, local binary patterns histograms, K-nearest neighbor, and convolutional neural network | 85.6%, 88.9% 81.4%, and 98.3% | 400 images for 40 persons |
| [42] | Local binary pattern | 93.3% and 90.8% | 30 images over 10 people, 5040 images over 120 people |
| [43] | Convolutional neural network and support vector machine | 97.5% | 1400 images for 200 persons |
| [54] | Virtual geometry group (VGG) face model | 92.1% | 2.6M images over 2.6K people |
| [55] | Nearest neighbor | 87.3% | 14,000 images of over 1000 people |
| [56] | Recurrent regression neural network | 95.6% | 4207 images for 337 persons |
| [57] | Binary quality assessment | 95.56% | 494 414 images for 10 575 persons |
| [58] | Eigenfaces, Fisherfaces, and Laplacian faces | 79.4%, 94.3%, and 95.4% | 41 368 images of 68 persons |
| [59] | SRC, NN, NS, and SVM | 98.4%, 72.7%, 94.4%, and 95.4% | 4000 images for 126 persons |
| [60] | Fisher vector space and deep face | 93.1% and 97.3% | 2.6M images of 2622 persons |
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