Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|
cifar10 alexnet | 1.24 | 0.8 | 2023 | 81 |
cifar10 autoencoder | 1.49 | 0.5 | 9073 | 53 |
cifar10 accuracy 90 | 1.97 | 0.5 | 4118 | 81 |
cifar10 augmentation | 0.52 | 0.8 | 8229 | 26 |
cifar 10 and cifar 100 | 1.45 | 0.2 | 5420 | 88 |
cifar10 autoencoder pytorch | 0.3 | 0.2 | 1380 | 9 |
cifar10 ae | 1.42 | 0.6 | 1903 | 16 |
cifar10 adam | 1.85 | 0.1 | 32 | 62 |
cifar10 adversarial examples | 1.58 | 0.3 | 8451 | 13 |
cifar10 alexnet pytorch | 0.57 | 0.5 | 8452 | 27 |
cifar10 augmentation pytorch | 1.35 | 0.4 | 1733 | 60 |
cifar10 high accuracy | 0.95 | 0.7 | 3244 | 79 |
cifar10 cnn architecture | 0.44 | 0.1 | 5284 | 14 |
mnist and cifar10 | 0.48 | 0.8 | 5816 | 48 |
cifar10 data augmentation | 0.12 | 0.4 | 4374 | 6 |
cifar10 mean and std | 1.83 | 0.3 | 992 | 89 |
cifar 10 alexnet tensorflow | 0.15 | 1 | 4831 | 5 |
cifar100 alexnet | 1.14 | 0.7 | 6076 | 88 |
alexnet cifar10 keras | 0.39 | 0.5 | 8406 | 36 |
fine tune alexnet pytorch cifar10 | 1.29 | 0.3 | 4182 | 4 |