From: ANINet: a deep neural network for skull ancestry estimation
Internet | AlexNet (%) | Vgg-16 (%) | GoogLenet (%) | Resnet-50 (%) | DenseNet-121 (%) | SqueezeNet (%) | ANINet (%) |
---|---|---|---|---|---|---|---|
Local projection | |||||||
Accuracy | 90.83 | 62.17 | 95.92 | 96.33 | 97.97 | 92.91 | 98.04 |
Precision | 89.38 | 69.70 | 96.11 | 96.74 | 97.98 | 93.76 | 98.76 |
Recall | 93.17 | 57.76 | 96.58 | 98.09 | 98.15 | 93.58 | 98.44 |
F1-score | 91.97 | 63.23 | 96.65 | 97.15 | 98.19 | 93.70 | 98.27 |
Specificity | 87.46 | 67.89 | 95.01 | 95.09 | 98.55 | 90.88 | 99.01 |
Global projection | |||||||
Accuracy | 95.04 | 60.78 | 96.08 | 98.03 | 98.09 | 95.91 | 98.21 |
Precision | 92.26 | 64.94 | 97.31 | 98.06 | 98.15 | 96.89 | 98.49 |
Recall | 96.27 | 57.68 | 94.41 | 98.38 | 98.43 | 96.47 | 98.51 |
F1-score | 94.80 | 61.17 | 95.96 | 98.50 | 98.70 | 96.80 | 98.77 |
Specificity | 92.01 | 62.31 | 93.69 | 97.98 | 98.85 | 93.00 | 99.09 |
Combining two projection methods | |||||||
Accuracy | 95.56 | 65.00 | 98.22 | 98.30 | 98.36 | 96.28 | 99.03 |
Precision | 92.97 | 69.92 | 97.32 | 98.49 | 98.57 | 97.04 | 98.82 |
Recall | 96.83 | 58.26 | 96.97 | 98.51 | 98.77 | 96.87 | 98.86 |
F1-score | 94.93 | 64.21 | 98.03 | 98.74 | 98.85 | 97.84 | 98.93 |
Specificity | 94.15 | 68.88 | 96.33 | 98.79 | 98.99 | 94.69 | 99.11 |