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Caffe

Caffe：一个快速开放的深度学习框架。（Caffe: a fast open framework for deep learning.）

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Caffe 是一个深度学习框架，考虑到了表达式、速度和模块化。它是由伯克利人工智能研究（BAIR）、伯克利视觉和学习中心（BVLC）和社区贡献者开发的。

查看项目网站，了解所有详情，例如

和分步示例。

自定义分发

社区

通过 https://gitter.im/BVLC/caffe 加入聊天。

请加入 caffe-users 群组 或 gitter 聊天，提出问题并讨论方法和模型。收集有关问题的框架开发讨论和详尽的错误报告。

酿造快乐吧！

许可和引用

Caffe 是根据 BSD 2-Clause license 许可发行的。 BAIR/BVLC 参考模型已发布，可以不受限制地使用。

如果它有助于您的研究，请在您的出版物中引用 Caffe： 

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}

Main metrics

Overview
Name With OwnerBVLC/caffe
Primary LanguageC++
Program languageCMake (Language Count: 8)
PlatformBSD, Linux, Mac, Windows, Docker
License:Other
所有者活动
Created At2013-09-12 18:39:48
Pushed At2024-07-31 23:10:28
Last Commit At2020-02-13 08:20:36
Release Count14
Last Release Name1.0 (Posted on )
First Release Namev0.1 (Posted on )
用户参与
Stargazers Count34.3k
Watchers Count2.1k
Fork Count18.6k
Commits Count4.2k
Has Issues Enabled
Issues Count4800
Issue Open Count898
Pull Requests Count1087
Pull Requests Open Count285
Pull Requests Close Count870
项目设置
Has Wiki Enabled
Is Archived
Is Fork
Is Locked
Is Mirror
Is Private

Caffe

Build Status
License

Caffe is a deep learning framework made with expression, speed, and modularity in mind.
It is developed by Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors.

Check out the project site for all the details like

and step-by-step examples.

Custom distributions

Community

Join the chat at https://gitter.im/BVLC/caffe

Please join the caffe-users group or gitter chat to ask questions and talk about methods and models.
Framework development discussions and thorough bug reports are collected on Issues.

Happy brewing!

License and Citation

Caffe is released under the BSD 2-Clause license.
The BAIR/BVLC reference models are released for unrestricted use.

Please cite Caffe in your publications if it helps your research:

@article{jia2014caffe,
  Author = {Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
  Journal = {arXiv preprint arXiv:1408.5093},
  Title = {Caffe: Convolutional Architecture for Fast Feature Embedding},
  Year = {2014}
}