articleNov 3, 2014Closed access

Caffe

Google (United States) · University of California, Berkeley · +1 more institution

Indexed incrossref

Abstract

Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. 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 ms per image). By separating model representation from actual implementation, Caffe allows experimentation and seamless switching among platforms for ease of development and…

Citation impact

11,189
total citations
FWCI
1099.31
Percentile
100%
References
11
Citations per year

Authors

8

Topics & keywords

Keywords
  • Computer science
  • Deep learning
  • Python (programming language)
  • CUDA
  • Artificial intelligence
  • Titan (rocket family)
  • Convolutional neural network
  • Software deployment
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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