Data augmentation project augumentation 만들어보기!
decalcomanie 형태로 만들어보자 cifar-100, cifar-10 은 대부분 데칼코마니 형태를 취해도 sementic이 유지가 되니까 잘 작동하지 않을까..?
| Dataset | DA | Acc |
|---|---|---|
| CIFAR-100 | MIXUP | 78.640 |
| CIFAR-100 | MIXUP(alpha=0.4) | 79.750 |
| CIFAR-100 | horizondecalcomanie | 76.670 |
| CIFAR-100 | random decalcomanie | 77.070 |
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Hi, I’m sorry to disturb you here. May I ask if you have successfully reproduced the pre-training model of SVT?
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