Software:Caffe
| Original author(s) | Yangqing Jia |
|---|---|
| Developer(s) | Berkeley Vision and Learning Center |
| Stable release | 1.0[1]
/ 18 April 2017 |
| Written in | C++ |
| Operating system | Linux, macOS, Windows[2] |
| Type | Library for deep learning |
| License | BSD[3] |
| Website | caffe |
| Machine learning and data mining |
|---|
 |
Caffe (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license.[4] It is written in C++, with a Python interface.[5]
History
Yangqing Jia created the Caffe project during his PhD at UC Berkeley.[6] It is currently hosted on GitHub.[7]
Features
Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully-connected neural network designs.[8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL.[9][10]
Applications
Caffe is being used in academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia. Yahoo! has also integrated Caffe with Apache Spark to create CaffeOnSpark, a distributed deep learning framework.[11]
Caffe2
In April 2017, Facebook announced Caffe2,[12] which included new features such as recurrent neural network (RNN). At the end of March 2018, Caffe2 was merged into PyTorch.[13]
See also
References
- ↑ "BVLC/caffe". 31 March 2020. https://github.com/BVLC/caffe.
- ↑ "Microsoft/caffe". GitHub. 30 March 2020. https://github.com/Microsoft/caffe.
- ↑ "caffe/LICENSE at master". GitHub. 31 March 2020. https://github.com/BVLC/caffe/blob/master/LICENSE.
- ↑ "BVLC/caffe". GitHub. 31 March 2020. https://github.com/BVLC/caffe/.
- ↑ "Comparing Frameworks: Deeplearning4j, Torch, Theano, TensorFlow, Caffe, Paddle, MxNet, Keras & CNTK". https://deeplearning4j.org/compare-dl4j-torch7-pylearn#caffe.
- ↑ "The Caffe Deep Learning Framework: An Interview with the Core Developers". Embedded Vision. 17 January 2016. http://www.embedded-vision.com/industry-analysis/technical-articles/caffe-deep-learning-framework-interview-core-developers.
- ↑ "Caffe: a fast open framework for deep learning.". GitHub. 31 March 2020. https://github.com/BVLC/caffe.
- ↑ "Caffe tutorial - vision.princeton.edu". Archived from the original on April 5, 2017. https://web.archive.org/web/20170405073658/https://vision.princeton.edu/courses/COS598/2015sp/slides/Caffe/caffe_tutorial.pdf.
- ↑ "Deep Learning for Computer Vision with Caffe and cuDNN". October 16, 2014. https://devblogs.nvidia.com/deep-learning-computer-vision-caffe-cudnn/.
- ↑ "mkl_alternate.hpp". https://github.com/BVLC/caffe/blob/3d5bed06a9b6b8a5dfd3db8da33f2fa3bc9a1213/include/caffe/util/mkl_alternate.hpp.
- ↑ "Yahoo enters artificial intelligence race with CaffeOnSpark". February 29, 2016. https://jaxenter.com/yahoo-enters-artificial-intelligence-race-with-caffeonspark-124324.html.
- ↑ Team, Caffe2 (April 18, 2017). "Caffe2 Open Source Brings Cross Platform Machine Learning Tools to Developers". http://caffe2.ai/blog/2017/04/18/caffe2-open-source-announcement.html.
- ↑ "Caffe2 Merges With PyTorch". May 16, 2018. https://medium.com/@Synced/caffe2-merges-with-pytorch-a89c70ad9eb7.
External links
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