Capsule Networks are a special type of artificial neural networks that better understand how parts of an object belong together.
Imagine a normal network only sees individual features, like lines or colors, but a Capsule Network also recognizes how these features are arranged in space relative to each other.
This allows it to capture an object more accurately, for example a face, even if it is shown from a different angle.
Capsule Networks help computers recognize images and objects better, even if they are rotated or shifted.
This makes them especially useful for applications like image recognition or robotics.