| 分类模型 | Accuracy | Recall | Specificity | FPR | F1 Score | Testing Time |
| VGG16 | 0.921851 | 0.921852 | 0.961459 | 0.014216 | 0.921852 | 482.572134 |
| VGG19 | 0.934197 | 0.934196 | 0.972811 | 0.013236 | 0.934196 | 579.018826 |
| GoogLeNet | 0.984818 | 0.984818 | 0.996965 | 0.003034 | 0.984796 | 116.845401 |
| ResNet18 | 0.987614 | 0.987615 | 0.997521 | 0.002478 | 0.987614 | 89.087674 |
| ResNet50 | 0.988413 | 0.988414 | 0.997682 | 0.002317 | 0.988418 | 252.264768 |
| ResNet101 | 0.990411 | 0.990412 | 0.998085 | 0.001914 | 0.990410 | 406.727547 |
| DenseNet121 | 0.998401 | 0.998402 | 0.999680 | 0.000319 | 0.998401 | 239.412328 |
| EfficientNet_b0 | 0.998401 | 0.998402 | 0.999681 | 0.000318 | 0.998402 | 154.782743 |
| MobileNet_v2 | 0.920894 | 0.920895 | 0.984175 | 0.015824 | 0.920979 | 116.050966 |
| ShuffleNet_v2 | 0.935277 | 0.935278 | 0.987059 | 0.012940 | 0.935206 | 60.194926 |