A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
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Updated
Nov 9, 2018 - Python
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
A curated list of awesome resources related to capsule networks
CapsNet (Capsules Net) in Geoffrey E Hinton paper "Dynamic Routing Between Capsules" - State Of the Art
Using Capsule Networks in GANS to generate very realistic fake images that could perhaps be used for deepfakes
A TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).
Hierarchical multi-label text classification of the BlurbGenreCollection using capsule networks.
A Clone version from Original SegCaps source code with enhancements on MS COCO dataset.
A tensorflow implementation of Hinton's [matrix capsules with EM routing](https://openreview.net/pdf?id=HJWLfGWRb)
A Capsule Network-based framework for identification of COVID-19 cases from chest X-ray Images
Recognition of Sign Language using Capsule Networks
Code for the Paper: "Conditional Variational Capsule Network for Open Set Recognition", Y. Guo, G. Camporese, W. Yang, A. Sperduti, L. Ballan, ICCV, 2021.
Prof. Geoffrey Hinton’ın “Dynamic Routing Between Capsules” makalesindeki Kapsül Ağı (Capsule Network: CapsNet) algoritmasının Keras Uygulamasıdır.
Global-Local Capsule Network (GLCapsNet) is a capsule-based architecture able to provide context-based eye fixation prediction for several autonomous driving scenarios, while offering interpretability both globally and locally.
PyTorch Implementation of "DeepCaps: Going Deeper with Capsule Networks" by Jathushan Rajasegaran et al.
Speech command recognition with capsule network & various NNs / KWS on Google Speech Command Dataset.
Capsule Networks and Convolutional Neural Networks for the Automated Segmentation of Left Atrium in Cardiac MRI
A collection of deep learning models (PyTorch implemtation)
🔷 Effects of Degradations on Deep Neural Network Architectures.
PyTorch Implementation of Capsule Networks in NIPS2017 and ICLR2018
"Capsule Networks against Medical Imaging Data Challenges" - LABELS@MICCAI 2018
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