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What is caffe?

Caffe is an open-source implementation of the recent convolutional algorithms that perform particularly well in large-scale image recognition tasks, such as the ImageNet Challenges. The purpose of caffe is to provide a reference implementation for such algorithms, and to enable wider adoption and analysis in the research community.

Caffe is written by Yangqing Jia at UC Berkeley as a replacement of decaf. It has then been adopted by several Berkeley vision group members and is under active development.