Merge pull request #111 from zalandoresearch/109-add-benchmark

fix #109

README.ja.md

@@ -156,6 +156,7 @@ scikit-learn ベースの自動ベンチマーキング・システムを構築
 |2 Conv Layers 113K parameters | Normalization | 0.922| 0.993 |[Abel G.](https://github.com/abelusha) | [:link:](https://github.com/abelusha/MNIST-Fashion-CNN/blob/master/Fashon_MNIST_CNN_using_Keras_10_Runs.ipynb)|
 |2 Conv Layers with 3 FC 1.8M parameters| Normalization | 0.932 | 0.994 | [@Xfan1025](https://github.com/Xfan1025) |[:link:](https://github.com/Xfan1025/Fashion-MNIST/blob/master/fashion-mnist.ipynb) |
 |2 Conv Layers with 3 FC 500K parameters | Augmentation, batch normalization | 0.934 | 0.994 | [@cmasch](https://github.com/cmasch) |[:link:](https://github.com/cmasch/zalando-fashion-mnist) |
+|2 Conv Layers+max pooling+dense+BN | None | 0.934 | - | [@khanguyen1207](https://github.com/khanguyen1207) | [:link:](https://github.com/khanguyen1207/My-Machine-Learning-Corner/blob/master/Zalando%20MNIST/fashion.ipynb)|
 |3 Conv Layers and 2 FC | None | 0.907 | - | [@Cenk Bircanoğlu](https://github.com/cenkbircanoglu) | [:link:](https://github.com/cenkbircanoglu/openface/tree/master/fashion_mnist)|
 |3 Conv Layers+pooling+BN | None | 0.903 | 0.994 | [@meghanabhange](https://github.com/meghanabhange) | [:link:](https://github.com/meghanabhange/FashionMNIST-3-Layer-CNN) |
 |3 Conv+pooling and 2 FC+dropout | None | 0.926 | - | [@Umberto Griffo](https://github.com/umbertogriffo) | [:link:](https://github.com/umbertogriffo/Fashion-mnist-cnn-keras)|

README.md

@@ -155,7 +155,8 @@ The table below collects the submitted benchmarks. Note that **we haven't yet te
 |2 Conv Layers net <100K parameters | None | 0.925 | 0.992 |[@hardmaru](https://twitter.com/hardmaru) | [:link:](https://github.com/hardmaru/pytorch_notebooks/blob/master/pytorch_tiny_custom_mnist_adam.ipynb)|
 |2 Conv Layers 113K parameters | Normalization | 0.922| 0.993 |[Abel G.](https://github.com/abelusha) | [:link:](https://github.com/abelusha/MNIST-Fashion-CNN/blob/master/Fashon_MNIST_CNN_using_Keras_10_Runs.ipynb)|
 |2 Conv Layers with 3 FC 1.8M parameters | Normalization | 0.932 | 0.994 | [@Xfan1025](https://github.com/Xfan1025) |[:link:](https://github.com/Xfan1025/Fashion-MNIST/blob/master/fashion-mnist.ipynb) |
-|2 Conv Layers with 3 FC 500K parameters | Augmentation, batch normalization | 0.934 | 0.994 | [@cmasch](https://github.com/cmasch) |[:link:](https://github.com/cmasch/zalando-fashion-mnist) | 
+|2 Conv Layers with 3 FC 500K parameters | Augmentation, batch normalization | 0.934 | 0.994 | [@cmasch](https://github.com/cmasch) |[:link:](https://github.com/cmasch/zalando-fashion-mnist) |
+|2 Conv Layers+max pooling+dense+BN | None | 0.934 | - | [@khanguyen1207](https://github.com/khanguyen1207) | [:link:](https://github.com/khanguyen1207/My-Machine-Learning-Corner/blob/master/Zalando%20MNIST/fashion.ipynb)| 
 |3 Conv Layers and 2 FC | None | 0.907 | - | [@Cenk Bircanoğlu](https://github.com/cenkbircanoglu) | [:link:](https://github.com/cenkbircanoglu/openface/tree/master/fashion_mnist)|
 |3 Conv Layers+pooling+BN | None | 0.903 | 0.994 | [@meghanabhange](https://github.com/meghanabhange) | [:link:](https://github.com/meghanabhange/FashionMNIST-3-Layer-CNN) |
 |3 Conv+pooling and 2 FC+dropout | None | 0.926 | - | [@Umberto Griffo](https://github.com/umbertogriffo) | [:link:](https://github.com/umbertogriffo/Fashion-mnist-cnn-keras)|

README.zh-CN.md

@@ -159,6 +159,7 @@ data = input_data.read_data_sets('data/fashion', source_url='http://fashion-mnis
 |2 Conv Layers net <100K parameters | None | 0.925 | 0.992 |[@hardmaru](https://twitter.com/hardmaru) | [:link:](https://github.com/hardmaru/pytorch_notebooks/blob/master/pytorch_tiny_custom_mnist_adam.ipynb)| 
 |2 Conv Layers with 3 FC 1.8M parameters | Normalization | 0.932 | 0.994 | [@Xfan1025](https://github.com/Xfan1025) |[:link:](https://github.com/Xfan1025/Fashion-MNIST/blob/master/fashion-mnist.ipynb) |
 |2 Conv Layers with 3 FC 500K parameters | Augmentation, batch normalization | 0.934 | 0.994 | [@cmasch](https://github.com/cmasch) |[:link:](https://github.com/cmasch/zalando-fashion-mnist) |
+|2 Conv Layers+max pooling+dense+BN | None | 0.934 | - | [@khanguyen1207](https://github.com/khanguyen1207) | [:link:](https://github.com/khanguyen1207/My-Machine-Learning-Corner/blob/master/Zalando%20MNIST/fashion.ipynb)|
 |2 Conv Layers 113K parameters | Normalization | 0.922| 0.993 |[Abel G.](https://github.com/abelusha) | [:link:](https://github.com/abelusha/MNIST-Fashion-CNN/blob/master/Fashon_MNIST_CNN_using_Keras_10_Runs.ipynb)|
 |3 Conv Layers and 2 FC | None | 0.907 | - | [@Cenk Bircanoğlu](https://github.com/cenkbircanoglu) | [:link:](https://github.com/cenkbircanoglu/openface/tree/master/fashion_mnist)|
 |3 Conv Layers+pooling+BN | None | 0.903 | 0.994 | [@meghanabhange](https://github.com/meghanabhange) | [:link:](https://github.com/meghanabhange/FashionMNIST-3-Layer-CNN) |