 The probability of the entity's presence in a specific input is the vector's length, while the vector's orientation quantifies the capsule's properties.Artificial neurons traditionally output a scalar, real-valued activation that loosely represents the probability of an observation.Capsnets replace scalar-output feature detectors with vector-output capsules and max-pooling with routing-by-agreement.