Convolutional Neural Networks (CNNs) are everywhere. In the last five years, we have seen a dramatic rise in the performance of visual recognition systems due to the introduction of deep architectures for feature learning and classification. CNNs have achieved good performance in a variety of areas, such as automatic speech understanding, computer vision, language translation, self-driving cars, and games such as Alpha Go. Thus, the applications of CNNs are almost limitless. DeepMind (from Google) recently published WaveNet, which uses a CNN to generate speech that mimics any human voice (https://deepmind.com/blog/wavenet-generative-model-raw-audio/).
In this chapter, we will cover the following topics:
- History of CNNs
- Overview of a CNN
- Image augmentation
