Capsule Network with Shortcut Routing

This study introduces "shortcut routing," a novel routing mechanism in capsule networks that addresses computational inefficiencies by directly activating global capsules from local capsules, eliminating intermediate layers. An attention-based approach with fuzzy coefficients is also explored for improved efficiency. Experimental results on Mnist, smallnorb, and affNist datasets show comparable classification performance, achieving accuracies of 99.52%, 93.91%, 89.02% respectively. The proposed fuzzy-based methods significantly reduce the number calculations 1.42 2.5 times compared to EM routing, highlighting their advantages networks. These findings contribute advancement efficient accurate hierarchical pattern representation models.