Capsule Network Performance on Complex Data

Understand

In recent years, convolutional neural networks (CNN) have played an important role in the field of deep learning.

• Variants of CNN's have proven to be very successful in classification tasks across different domains.
• However, there are two big drawbacks to CNN's: their failure to take into account of important spatial hierarchies between features, and their lack of rotational invariance.
• As long as certain key features of an object are present in the test data, CNN's classify the test data as the object, disregarding features' relative spatial orientation to each other.