Convolutional networks (and CapsNET) for SuperNEMO tracker
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Updated
Nov 2, 2023 - Python
Convolutional networks (and CapsNET) for SuperNEMO tracker
EasyNodule is a software made to help clinicinas to classify Lung Cancer. This will help in elaborating a traitement for the patient which will reduce the progress of the cancer which considered the most killer cancer in the world.
Capsule Network Implementation
A TensorFlow implementation of "Matrix Capsules with EM Routing" by Hinton et al. (2018).
A novel data augmentation method based on Cycle-GAN, and a new offline handwritten signature verification system based on CapsNet.
CapsLayer: An advanced library for capsule theory
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)
Repositório com a parte prática do meu Trabalho de Conclusão de Curso III, referente ao algoritmo da arquitetura CapsNet para a classificação de imagens de retina em glaucomatosas e normais.
🎆 A visualization of the CapsNet layers to better understand how it works
Melanoma recognition via dynamic routing between capsules
Official Pytorch code for (AAAI 2020) paper "Capsule Routing via Variational Bayes", https://arxiv.org/pdf/1905.11455.pdf
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
A Keras implementation of CapsNet in NIPS2017 paper "Dynamic Routing Between Capsules". Now test error = 0.34%.
"Capsule Networks against Medical Imaging Data Challenges" - LABELS@MICCAI 2018
Unofficial implementation of Capsule Networks, Dynamic Routing between capsules (by tensorflow)
[NO MAINTENANCE INTENDED] A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules".
PyTorch implementation of Geoffrey Hinton's Dynamic Routing Between Capsules
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