# Capsule network with shortcut routing

arXiv: https://arxiv.org/abs/2307.10212 · HTML: https://mlsanity.com/paper/2307.10212/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 22 of its 32 references that are in the map.
- First posted on arXiv 14 Jul 2023.

## Builds on (most cited first, 22 of 22)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Explaining and Harnessing Adversarial Examples](https://mlsanity.com/paper/1412.6572/) (2014)
- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Spatial Transformer Networks](https://mlsanity.com/paper/1506.02025/) (2015)
- [Group Equivariant Convolutional Networks](https://mlsanity.com/paper/1602.07576/) (2016)
- [Dynamic Routing Between Capsules](https://mlsanity.com/paper/1710.09829/) (2017)
- [Harmonic Networks: Deep Translation and Rotation Equivariance](https://mlsanity.com/paper/1612.04642/) (2016)
- [Deep Convolutional Inverse Graphics Network](https://mlsanity.com/paper/1503.03167/) (2015)
- [3D Point Capsule Networks](https://mlsanity.com/paper/1812.10775/) (2018)
- [Stacked Capsule Autoencoders](https://mlsanity.com/paper/1906.06818/) (2019)
- [DeepCaps: Going Deeper with Capsule Networks](https://mlsanity.com/paper/1904.09546/) (2019)
- [Group Equivariant Capsule Networks](https://mlsanity.com/paper/1806.05086/) (2018)
- [Capsules for Object Segmentation](https://mlsanity.com/paper/1804.04241/) (2018)
- [VideoCapsuleNet: A Simplified Network for Action Detection](https://mlsanity.com/paper/1805.08162/) (2018)
- [Investigating Capsule Networks with Dynamic Routing for Text Classification](https://mlsanity.com/paper/1804.00538/) (2018)
- [Brain Tumor Type Classification via Capsule Networks](https://mlsanity.com/paper/1802.10200/) (2018)
- [Attention routing between capsules](https://mlsanity.com/paper/1907.01750/) (2019)
- [CapProNet: Deep Feature Learning via Orthogonal Projections onto Capsule Subspaces](https://mlsanity.com/paper/1805.07621/) (2018)
- [Neural Network Encapsulation](https://mlsanity.com/paper/1808.03749/) (2018)
- [Fast Dynamic Routing Based on Weighted Kernel Density Estimation](https://mlsanity.com/paper/1805.10807/) (2018)
- [Multi-labeled Relation Extraction with Attentive Capsule Network](https://mlsanity.com/paper/1811.04354/) (2018)
- [Convolutional capsule network for classification of breast cancer histology images](https://mlsanity.com/paper/1804.08376/) (2018)

## Abstract (arXiv)

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%, and 89.02% respectively. The proposed fuzzy-based and attention-based routing methods significantly reduce the number of calculations by 1.42 and 2.5 times compared to EM routing, highlighting their computational advantages in capsule networks. These findings contribute to the advancement of efficient and accurate hierarchical pattern representation models.