Caffe

Caffe is an open-source deep learning framework developed by the Berkeley Vision and Learning Center (BVLC). It is designed for speed, modularity, and expressiveness, making it suitable for both research and production environments. Caffe supports various architectures for convolutional neural networks (CNNs) and is particularly popular in image classification tasks. Its efficient performance and ease of use have led to widespread adoption in computer vision applications, including image recognition and segmentation.