Caffe
Frameworks
Caffe

Provides a deep learning framework Caffe, suitable for visual recognition tasks, developed by the Berkeley Vision and Learning Center.

【Application Scenarios】

  • Work scenarios: Deep learning research and industrial applications
  • Life scenarios: Image classification, style recognition, and other multimedia applications

【Target Users】

  • Academic researchers
  • Startup company prototype developers
  • Industrial application developers

【Core Features】

  • Provides a deep learning framework with strong expressiveness, fast speed, and modularity
  • Supports seamless switching between CPU and GPU
  • Offers a wealth of pre-trained models and tutorials

【Is It Free】

  • Yes, under the BSD 2-Clause license

【Community Ecosystem】

  • Active open-source community, with over 1,000 developers contributing
  • Provides caffe-users groups and Github platform for user exchange and contributions

【Summary】

  • Caffe is a deep learning framework developed by Berkeley AI Research (BAIR), renowned for its expressive architecture, scalable code, and high-speed processing capabilities, suitable for academic research and industrial applications.
  • It supports a wide range of deep learning tasks, including image classification, style recognition, etc., and has an active open-source community.
Content assisted by AI. Please review carefully.

Related Navigation