How AI Can See Better Than Your Eyes Do
Convolutional Neural Networks explained, in plain English.
In this article, we introduce the key ideas in modern computer vision. We explore how to stack several layers with hundreds of neurons that learn low-level features in images. We motivate our quest by first looking at how vision works on mammals.
Vision, made in Nature
Neurons in the visual cortex of mammals are organized to process images in layers, some of which has a particular function at recognizing localized features such as lines and edges; some layers are activated when position and orientation change; other layers react to complex shapes such as crossing lines.
This motivates stacked convolutional layers, which consists of restricting the visual field of every neuron to a small area of the input image. The size of the receptive field is given by the filter size, also called kernel size. When the filter slides through the image, it works like a convolution in signal processing, therefore it allows features detection.
