Caffe (software)

Caffe is a deep learning framework used for large-scale product cases. It useshas C++expression, asit itsis codebasefast and modular. Caffe was first used for conventional convolutional neural network (CNN) applications.

Its framework is BSD-licensed C++ library with Python and MATLAB bindings for training and deploying general purpose convolutional neural networks.

Yangqing Jia created Caffe and Berkeley AI Research (BAIR) together with community contributors developed Caffe.

Caffe powers ongoing research projects, large-scale industrial applications and startup prototypes in vision, speech, and multimedia.

Caffe is an open source deep learning framework written in C++, with a Python interface. Developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license 18 April 2017.

Expressive structure encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then expand to commodity clusters or mobile devices.

Caffe is a deep learning framework used for large-scale product cases. It uses C++ as its codebase. Caffe was first used for conventional convolutional neural network (CNN) applications.

Caffe is aan open source deep learning framework. An open source and written in C++, with a Python interface. Developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license 18 April 2017.

Caffe is a deep learning framework. It is open source and written in C++, with a Python interface.

ItCaffe is developeda deep learning framework. An open source and written in C++, with a Python interface. Developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license 18 April 2017.

Expressive structure encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deployexpand to commodity clusters or mobile devices.

Caffe is a deep learning framework. It is open source and written in C++, with a Python interface.

It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license.

Expressive structure encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices.