In this article, we will discuss multiple perspectives that involve the receptive field of a deep convolutional architecture. We will address the influence of the receptive field starting for the human visual system. As you will see, a lot of terminology of deep learning comes from neuroscience. As a short motivation, convolutions are awesome but it is not enough just to understand how it works. The idea of the receptive field will help you dive into the architecture that you are using or developing. If you are looking for an in-depth analysis to understand how you can calculate the receptive field of your model as well as the most effective ways to increase it, this article was made for you. In the end, fundamentals are to be mastered!
