In this chapter, we learned about the different CNN architectures. These models are pre-trained existing models and differ in network architecture. Each of these networks is designed to solve a problem specific to its architecture. So, here we described their architectural differences.

We also understood how our own CNN architecture, as defined in the previous chapter, differs from these advanced ones.

In the next chapter, we will learn how these pre-trained models can be used for transfer learning.