This branch is merged to IntelLabs/SkimCaffe and not maintained anymore. The related work is published in ICLR 2017:

@incollection{Jongsoo_ICLR2017,
Title = {Faster CNNs with Direct Sparse Convolutions and Guided Pruning},
Author = {Park, Jongsoo and Li, Sheng and Wen, Wei and Tang, Tak Peter, Ping and Li, Hai and Chen, Yiran and Dubey, Pradeep},
bookTitle = {ICLR},
Year = {2017}
}

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

Check out the project site for all the details like

• DIY Deep Learning for Vision with Caffe
• Tutorial Documentation
• BVLC reference models and the community model zoo
• Installation instructions

and step-by-step examples.

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!

Caffe is released under the BSD 2-Clause license. The 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}
}