Classification On Indl
指标
Average Recall
结果
各模型在此基准测试上的性能结果
| 论文标题 | 代码 | ||
|---|---|---|---|
| ConvNext | 93.47% | A ConvNet for the 2020s | |
| VGG16 | 92.86% | Very Deep Convolutional Networks for Large-Scale Image Recognition | |
| DenseNet201 | 90.99% | Densely Connected Convolutional Networks | |
| Inception ResNet V2 | 90.27% | Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning | |
| Xception | 89.81% | Xception: Deep Learning with Depthwise Separable Convolutions | |
| NASNetLarge | 89.52% | Learning Transferable Architectures for Scalable Image Recognition | |
| Darknet53 | 88.53% | YOLOv3: An Incremental Improvement | |
| ResNetV2_50 | 88.08% | ResNet strikes back: An improved training procedure in timm | |
| MobileNetV3 | 84.28% | Searching for MobileNetV3 |
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