CapsLayer

CapsLayer:胶囊理论的高级库。(CapsLayer: An advanced library for capsule theory)

Github星跟蹤圖

CapsLayer: An advanced library for capsule theory

Capsule theory is a potential research proposed by Geoffrey E. Hinton et al, where he describes the shortcomings of the Convolutional Neural Networks and how Capsules could potentially circumvent these problems such as "pixel attack" and create more robust Neural Network Architecture based on Capsules Layer.

We expect that this theory will definitely contribute to Deep Learning Industry and we are excited about it. For the same reason we are proud to introduce CapsLayer, an advanced library for the Capsule Theory, integrating capsule-relevant technologies, providing relevant analysis tools, developing related application examples, and probably most important thing: promoting the development of capsule theory.

This library is based on Tensorflow and has a similar API with it but designed for capsule layers/models.

Features

If you want us to support more features, let us know by opening Issues or sending E-mail to naturomics.liao@gmail.com

Documentation

Contributions

Feel free to send your pull request or open issues

Citation

If you find it is useful, please cite our project by the following BibTex entry:

@misc{HuadongLiao2017,
title = {CapsLayer: An advanced library for capsule theory},
author = {Huadong Liao, Jiawei He},
year = {2017}
publisher = {GitHub},
journal = {GitHub Project},
howpublished = {\url{http://naturomics.com/CapsLayer}},
}

Note:
We are considering to write a paper for this project, but before that, please cite the above Bibtex entry if you find it helps.

License

Apache 2.0 license.

主要指標

概覽
名稱與所有者naturomics/CapsLayer
主編程語言Python
編程語言Python (語言數: 2)
平台BSD, Linux, Mac, Windows
許可證Apache License 2.0
所有者活动
創建於2017-11-26 08:54:22
推送於2022-01-21 09:44:07
最后一次提交2022-01-21 17:44:06
發布數0
用户参与
星數360
關注者數39
派生數115
提交數50
已啟用問題?
問題數39
打開的問題數17
拉請求數6
打開的拉請求數2
關閉的拉請求數5
项目设置
已啟用Wiki?
已存檔?
是復刻?
已鎖定?
是鏡像?
是私有?