sh install.sh
python train.py
| Name | Precision |
|---|---|
| Cifar10Classifier_01 | 83.11% |
| Cifar10Classifier_02 | 87.00% |
| Cifar10Classifier_03 | 87.25% |
| Cifar10Classifier_04 | 87.67% |
| Cifar10Classifier_05 | 87.17% |
| Cifar10Classifier_06 | 86.74% |
| Cifar10Classifier_07 | 86.17% |
| Name | Description |
|---|---|
| GPU | GeForce GTX TITAN X |
| OS | Ubuntu 16.04 LTS |
| Library | TensorFlow 0.8.0 |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 256 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
| Layer Type | Parameters |
|---|---|
| input | size:28x28, channels:1 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| normalizing | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:64, padding:1 |
| relu | |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| convolution | kernel:3x3, channels:128, padding:1 |
| relu | |
| normalizing | |
| convolution | kernel:3x3, channels:256, padding:1 |
| relu | |
| max pooling | kernel:2x2, strides: 2 |
| linear | channels: 1024 |
| relu | |
| normalizing | |
| dropout | rate: 0.5 |
| linear | channels: 256 |
| relu | |
| dropout | rate: 0.5 |
| linear | channels: 10 |
| relu | |
| softmax |
- [1]. He, Kaiming, et al. "Deep Residual Learning for Image Recognition." arXiv preprint arXiv:1512.03385 (2015).