Caffe (Convolutional Architecture for Fast Feature Embedding) is a

deep learning Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. ...

framework, originally developed at

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. It is

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, under a

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. It is written in C++, with a Python interface.

History

Yangqing Jia created the Caffe project during his PhD at UC Berkeley. It is currently hosted on

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Features

Caffe supports many different types of deep learning architectures geared towards

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and image segmentation. It supports CNN, RCNN, LSTM and fully connected neural network designs. Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as

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cuDNN and Intel MKL.

Applications

Caffe is being used in academic research projects, startup prototypes, and even large-scale industrial applications in vision, speech, and multimedia.

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has also integrated Caffe with

Apache Spark Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of Califor ...

to create CaffeOnSpark, a distributed deep learning framework.

Caffe2

In April 2017,

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announced Caffe2, which included new features such as Recurrent Neural Networks. At the end of March 2018, Caffe2 was merged into PyTorch.

References

External links