Caffe is a powerful deep learning framework designed for expression, speed, and modularity.
Developed by Berkeley AI Research (BAIR) and a vibrant community, it offers an expressive architecture that encourages innovation without hard-coding, enabling seamless switching between CPU and GPU for training and deployment.
With extensible code and active development from a diverse group of contributors, Caffe boasts speed, processing over 60M images per day with a single NVIDIA K40 GPU.
This framework is ideal for research experiments and industry deployment, empowering projects in vision, speech, and multimedia. Join the thriving Caffe community for academic research, startup prototypes, and large-scale industrial applications.
