Effectiveness of the Recent Advances in Capsule Networks

Nidhin Harilal, Rohan Prashant Patil

Abstract:

Convolutional neural networks (CNNs) have revolutionized the field of deep neural
networks. However, recent research has shown that CNNs fail to generalize under
various conditions and hence the idea of capsules was introduced in 2011, though
the real surge of research started from 2017. In this paper, we present an overview of
the recent advances in capsule architecture and routing mechanisms. In addition, we
find that the relative focus in recent literature is on modifying routing procedure or
architecture as a whole but the study of other finer components, specifically, squash
function is wanting. Thus, we also present some new insights regarding the effect
of squash functions in performance of the capsule networks. Finally, we conclude
by discussing and proposing possible opportunities in the field of capsule networks.