Caffe_(software)

Caffe (software)

Caffe (software)

Deep learning framework


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]

Quick Facts Original author(s), Developer(s) ...

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

  1. "BVLC/caffe". GitHub. 31 March 2020.
  2. "Microsoft/caffe". GitHub. 30 March 2020.
  3. "caffe/LICENSE at master". GitHub. 31 March 2020.
  4. "BVLC/caffe". GitHub. 31 March 2020.
  5. "Caffe tutorial - vision.princeton.edu" (PDF). Archived from the original (PDF) on April 5, 2017.
  6. "Deep Learning for Computer Vision with Caffe and cuDNN". NVIDIA Developer Blog. October 16, 2014.
  7. "mkl_alternate.hpp". BVLC Caffe. Retrieved 2018-04-11.
  8. Team, Caffe2 (April 18, 2017). "Caffe2 Open Source Brings Cross Platform Machine Learning Tools to Developers". Caffe2.{{cite web}}: CS1 maint: numeric names: authors list (link)
  9. "Caffe2 Merges With PyTorch". Medium. May 16, 2018.

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