Caffe: Convolutional Architecture for Fast Feature Embedding

20 Jun 2014Yangqing Jia • Evan Shelhamer • Jeff Donahue • Sergey Karayev • Jonathan Long • Ross Girshick • Sergio Guadarrama • Trevor Darrell

The framework is a BSD-licensed C++ library with Python and MATLAB bindings for training and deploying general-purpose convolutional neural networks and other deep models efficiently on commodity architectures. Caffe fits industry and internet-scale media needs by CUDA GPU computation, processing over 40 million images a day on a single K40 or Titan GPU ($\approx$ 2.5 ms per image). By separating model representation from actual implementation, Caffe allows experimentation and seamless switching among platforms for ease of development and deployment from prototyping machines to cloud environments.

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