Capsule Network Explainability Explained for Beginners

Capsule Network Explainability deals with understanding what a capsule network actually learns and how it makes decisions.

Capsule networks are special neural networks that can capture information about objects and their parts better than conventional networks.

Explainability means being able to understand why the network makes a certain prediction, for example why it recognizes an image as a cat.

This helps to build trust in the technology and to better identify errors.