Created
October 31, 2017 15:35
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3. build a network
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| model = Sequential() | |
| model.add(Conv2D(32, (3, 3), input_shape=(28,28,1))) | |
| model.add(Activation('relu')) | |
| BatchNormalization(axis=-1) | |
| model.add(Conv2D(32, (3, 3))) | |
| model.add(Activation('relu')) | |
| model.add(MaxPooling2D(pool_size=(2,2))) | |
| BatchNormalization(axis=-1) | |
| model.add(Conv2D(64,(3, 3))) | |
| model.add(Activation('relu')) | |
| BatchNormalization(axis=-1) | |
| model.add(Conv2D(64, (3, 3))) | |
| model.add(Activation('relu')) | |
| model.add(MaxPooling2D(pool_size=(2,2))) | |
| model.add(Flatten()) | |
| # Fully connected layer | |
| BatchNormalization() | |
| model.add(Dense(512)) | |
| model.add(Activation('relu')) | |
| BatchNormalization() | |
| model.add(Dropout(0.2)) | |
| model.add(Dense(10)) | |
| model.add(Activation('softmax')) |
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