Caffe is an open-source deep learning framework designed for speed and modularity. Developed by Berkeley AI Research (BAIR), it is widely used in AI and machine learning applications, particularly for image classification and convolutional neural networks (CNNs). Caffe's efficient architecture enables rapid prototyping and large-scale deployment of deep learning models