Convolution Neural Network

Convolution Neural Networks

Use Cases: Image processing, Facial recognition, Computer Vision

Convolution Neural Networks are unique because they’re created in mind that the input will be an image. CNNs perform a sliding window function to a matrix. The window is called a kernel and it slides across the image creating a convolved feature.

Creating a convolved feature allows for edge detection which then allows for a network to depict objects from pictures.

edge detection from GIMP manual

The convolved feature to create this looks like this matrix below:

Convolved feature from GIMP manual

Here’s a sample of code to identify handwritten digits from the MNIST dataset.