擅长:python、mysql、java
<p>def make_CNN_model():</p>
<pre><code>model = Sequential()
# input layer transformation (BatchNormalization + Dropout)
model.add(layers.BatchNormalization(name='inputlayer',input_shape=(28,28,1)))
model.add(layers.Dropout(name='Droupout_inputlayer',rate=0.3))
# convolutional layer (Conv2D + MaxPooling2D + Flatten + Dropout)
model.add(layers.Conv2D(filters=32,activation='relu', name="Convoluationlayer_1",kernel_size=(3,3),border_mode='same'))
model.add(layers.MaxPooling2D(name='MaxPooling_1'))
model.add(layers.Flatten(name="Flaten_1"))
model.add(layers.Dropout(rate=0.3))
# fully connected layer (Dense + BatchNormalization + Activation + Dropout)
model.add(layers.Dense(name="FullyConnectedLayer_1",units=50))
model.add(layers.BatchNormalization())
model.add(layers.Activation('relu'))
model.add(layers.Dropout(rate=0.3))
# output layer (Dense + BatchNormalization + Activation)
model.add(layers.Dense(name = "Outputlayer", units=10))
model.add(layers.BatchNormalization())
model.add(layers.Activation('sigmoid'))
return model
</code></pre>