Why Convolve? : Understanding Convolution and Feature Extraction in Deep Networks

An Explanation of 1D/2D Convolution, its Role in Feature Learning, and a Visualization Tool

Figure 1: 1D/2D Convolutions and an Interactive Visualization Tool (Source: Author)

It is a common practice nowadays to construct deep neural networks with a set of convolution layers. However, it was not always like this, earlier neural networks and other machine learning frameworks didn’t employ convolutions. Feature extraction and learning were two separate fields of study until recently. This is why it is important to understand how Convolution works and why it took such an important place in deep learning architectures. In this article we shall explore the Convolution thoroughly and you would be able to understand the concept more deeply with an interactive tool.