Hands-On Deep Learning Algorithms with Python

Inception v2 and v3

Inception v2 and v3 are introduced in the paper, Going Deeper with Convolutions by Christian Szegedy as mentioned in Further reading section. The authors suggest the use of factorized convolution, that is, we can break down a convolutional layer with a larger filter size into a stack of convolutional layers with a smaller filter size. So, in the inception block, a convolutional layer with a 5 x 5 filter can be broken down into two convolutional layers with 3 x 3 filters, as shown in the following diagram. Having a factorized convolution increases performance and speed:

The authors also suggest breaking down a convolutional ...