Primary Capsule

• lowest layer of a capsule network
• processing the raw input image
• Each capsule in the primary layer is sensitive to a specific feature of the input image, such as an edge or a particular shape.

Convolution

• The primary capsules in a capsule network are created by applying a series of convolutional filters to the input image. Each filter is responsible for detecting a specific feature in the input image, such as an edge or a particular shape.

Reshape

• The outputs of the convolutional filters are then reshaped into a grid of “capsules,” each of which corresponds to a specific location in the input image.

Squash

• The outputs of the capsules are then “squashed” to ensure that they have a non-negative scalar value, which allows the network to learn more easily to differentiate between objects and background.