Neural Architecture Search On Food 101
评估指标
Accuracy (%)
FLOPS
PARAMS
评测结果
各个模型在此基准测试上的表现结果
模型名称 | Accuracy (%) | FLOPS | PARAMS | Paper Title | Repository |
|---|---|---|---|---|---|
| NAT-M2 | 88.5 | 266M | 4.1M | Neural Architecture Transfer | |
| Balanced Mixture | - | - | - | Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture | |
| NAT-M1 | 87.4 | 198M | 3.1M | Neural Architecture Transfer | |
| NAT-M4 | 89.4 | 361M | 4.5M | Neural Architecture Transfer | |
| NAT-M3 | 89.0 | 299M | 3.9M | Neural Architecture Transfer |
0 of 5 row(s) selected.