Neural Architecture Search On Food 101
평가 지표
Accuracy (%)
FLOPS
PARAMS
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | 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 |
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