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awesome-capsule-networks - A curated list of awesome resources related to capsule networks


A curated list of awesome resources related to capsule networks maintained by AI Summary. Please pull a request if you are aware of additional resources.

capsule-net-pytorch - A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules"

  •    Python

The current test error is 0.21% and the best test error is 0.20%. The current test accuracy is 99.31% and the best test accuracy is 99.32%. A Capsule is a group of neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or object part.


  •    Python

This repository contains different tests performed on a capsule network model. Example code to train the capsule_dynamic(CapsNet with dynamic routing) model on mnist dataset.

capsnet-traffic-sign-classifier - A Tensorflow implementation of CapsNet(Capsules Net) apply on german traffic sign dataset

  •    Jupyter

This implementation is based on this paper: Dynamic Routing Between Capsules (https://arxiv.org/abs/1710.09829) from Sara Sabour, Nicholas Frosst and Geoffrey E. Hinton. During the training, the checkpoint is saved by default into the outputs/checkpoints/ folder. The exact path and name of the checkpoint is print during the training.

Hands-On-Deep-Learning-Algorithms-with-Python - Hands-On Deep Learning Algorithms with Python, By Packt

  •    Jupyter

This is the code repository for Hands-On Deep Learning Algorithms with Python, published by Packt. Deep learning is one of the most popular domains in the AI space, allowing you to develop multi-layered models of varying complexities.