CapsLayer

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

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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.

主要指标

概览
名称与所有者naturomics/CapsLayer
主编程语言Python
编程语言Python (语言数: 2)
平台BSD, Linux, Mac, Windows
许可证Apache License 2.0
所有者活动
创建于2017-11-26 08:54:22
推送于2022-01-21 09:44:07
最后一次提交2022-01-21 17:44:06
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