# 其他模型

## 概述
正在持续更新中......


## 精度、FLOPS和参数量

| Models                    | Top1   | Top5   | Reference<br>top1 | Reference<br>top5 | FLOPS<br>(G) | Parameters<br>(M) |
|:--:|:--:|:--:|:--:|:--:|:--:|:--:|
| AlexNet                   | 0.567  | 0.792  | 0.5720            |                   | 1.370        | 61.090            |
| SqueezeNet1_0             | 0.596  | 0.817  | 0.575             |                   | 1.550        | 1.240             |
| SqueezeNet1_1             | 0.601  | 0.819  |                   |                   | 0.690        | 1.230             |
| VGG11                     | 0.693  | 0.891  |                   |                   | 15.090       | 132.850           |
| VGG13                     | 0.700  | 0.894  |                   |                   | 22.480       | 133.030           |
| VGG16                     | 0.720  | 0.907  | 0.715             | 0.901             | 30.810       | 138.340           |
| VGG19                     | 0.726  | 0.909  |                   |                   | 39.130       | 143.650           |
| DarkNet53                 | 0.780  | 0.941  | 0.772             | 0.938             | 18.580       | 41.600            |
| ResNet50_ACNet            | 0.767  | 0.932  |                   |                   | 10.730       | 33.110            |
| ResNet50_ACNet<br>_deploy | 0.767  | 0.932  |                   |                   | 8.190        | 25.550            |



## FP32预测速度


| Models                 | Crop Size | Resize Short Size | Batch Size=1<br>(ms) |
|---------------------------|-----------|-------------------|----------------------|
| AlexNet                   | 224       | 256               | 1.176                |
| SqueezeNet1_0             | 224       | 256               | 0.860                |
| SqueezeNet1_1             | 224       | 256               | 0.763                |
| VGG11                     | 224       | 256               | 1.867                |
| VGG13                     | 224       | 256               | 2.148                |
| VGG16                     | 224       | 256               | 2.616                |
| VGG19                     | 224       | 256               | 3.076                |
| DarkNet53                 | 256       | 256               | 3.139                |
| ResNet50_ACNet<br>_deploy | 224       | 256               | 5.626                |