|Original author(s)||Yangqing Jia|
|Developer(s)||Berkeley Vision and Learning Center|
1.0 / 18 April 2017
|Operating system||Linux, macOS, Windows|
|Type||Library for deep learning|
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. Caffe supports GPU based accleration using CuDNN of Nvidia.
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.
- "Release 1.0".
- "Microsoft/caffe". GitHub.
- "caffe/LICENSE at master". GitHub.
- "BVLC/caffe". GitHub.
- "Comparing Frameworks: Deeplearning4j, Torch, Theano, TensorFlow, Caffe, Paddle, MxNet, Keras & CNTK".
- "The Caffe Deep Learning Framework: An Interview with the Core Developers". Embedded Vision.
- "Caffe: a fast open framework for deep learning.". GitHub.
- "Caffe tutorial - vision.princeton.edu" (PDF). Archived from the original (PDF) on April 5, 2017.
- "Deep Learning for Computer Vision with Caffe and cuDNN".
- "Yahoo enters artificial intelligence race with CaffeOnSpark".
- "Caffe2 Open Source Brings Cross Platform Machine Learning Tools to Developers".
- Official website (GitHub)