Easy to use: Caffe has a simple C++ code structure and a user-friendly Python interface, allowing users to quickly get started with deep learning tasks.
Flexibility: Caffe supports various types of neural network architectures including convolutional neural networks, recurrent neural networks, etc., allowing users to flexibly build and train neural networks according to their needs.
Efficiency: Caffe was designed with optimization for speed and memory usage in mind, allowing for high efficiency when training neural networks on large datasets.
Community support: Caffe has a large user community and development team, where users can access support and help, as well as contribute to the development and improvement of Caffe.
Scalability: Caffe offers a variety of plugins and extension interfaces, allowing users to customize and expand Caffe according to their needs.