Chapter 3: Deep CNN Architectures
In this chapter, we will first briefly review the evolution of CNNs (in terms of architectures), and then we will study the different CNN architectures in detail. We will implement these CNN architectures using PyTorch and in doing so, we aim to exhaustively explore the tools (modules and built-in functions) that PyTorch has to offer in the context of building Deep CNNs. Building strong CNN expertise in PyTorch will enable us to solve a number of deep learning problems involving CNNs. This will also help us in building more complex deep learning models or applications of which CNNs are a part.
This chapter will cover the following topics:
- Why are CNNs so powerful?
- Evolution of CNN architectures
- Developing LeNet from scratch
- Fine-tuning the AlexNet model
- Running a pre-trained VGG model
- Exploring GoogLeNet and Inception v3
- Discussing ResNet and DenseNet architectures
- Understanding EfficientNets and the future of...
