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Introduction to how CNNs Work

Convolutional Neural Networks

• Now, the best way to explain a convolutional layer is to imagine a flashlight that is shining over the top left of the image. In order to understand how this works, imagine as if a flashlight shines its light and covers a 5 x 5 area. And now, let’s imagine this flashlight sliding across all the areas of the input image. This flashlight is called a filter(or sometimes referred to as a neuron or a kernel) and the region that it is shining over is called the receptive field. This filter is also an array of numbers (the numbers are called weights or parameters).
• Image에 대해 weights를 가진 filter를 한칸씩 움직이면서 filter의 weights와 pixel 값을 element-wise하게 곱하고, filter에 대한 해당 곱의 합을 convolved feature로 취함