title: Why is the number of filters in CNNs usually an even number?
body: <p>When choosing a number of filters in convolutional neural network architectures, the number of filters is an even number. For example, these are the numbers of filters in convolutional layers in AlexNet:</p>
  
  <pre><code>conv1 - 96, 
  conv2 - 256, 
  conv3 - 384, 
  conv4 - 384, 
  conv5 - 256.
  </code></pre>
  
  <p>Is there any rationale behind the filter numbers being the even numbers?</p>