WTF is image classification? (Conquering neural networks for the curious)

A CNN has
Convolutional layers
ReLU layers
Pooling layers
a Fully connected layer

A classic CNN architecture would look something like this:
Input -Convolution -ReLU -Convolution -ReLU -Pooling –
ReLU -Convolution -ReLU -Pooling -Fully Connected
A CNN convolves (not convolutes…) learned features with input data and uses 2D convolutional layers. GIF via GIPHYA CNN
starts with an input image
applies many different filters to it to create a feature map
applies a ReLU function to increase non-linearity
applies a pooling layer to each feature map
flattens the pooled images into one long vector. You take the filter and apply it pixel block by pixel block to the input image.

Source: towardsdatascience.com