title: what is the meaning of (axis = 3) in the BatchNormalization?
body: <pre><code>inputs = Input((img_height, img_width, img_ch))
  conv1 = Conv2D(n_filters, (k, k), padding=padding)(inputs)
  conv1 = BatchNormalization(scale=False, axis=3)(conv1)
  conv1 = Activation('relu')(conv1)    
  conv1 = Conv2D(n_filters, (k, k),  padding=padding)(conv1)
  conv1 = BatchNormalization(scale=False, axis=3)(conv1)
  conv1 = Activation('relu')(conv1)    
  pool1 = MaxPooling2D(pool_size=(s, s))(conv1)
  </code></pre>
  
  <p>What is the meaning of (axis =3) in the <code>BatchNormalization</code>  I read keras documentation but I coudln't understand it, can any one explain what does axis means? </p>