A Region Proposal Network (RPN) is a component of certain object detection systems, particularly in the Faster R-CNN framework. It is designed to efficiently propose candidate object bounding boxes from an input image. The RPN uses a convolutional neural network to analyze features and generate region proposals, which are potential locations where objects may be found. The RPN operates by sliding a small network over the feature map produced by a backbone network, such as ResNet. It predicts both the objectness score, indicating the likelihood of an object being present, and the bounding box coordinates for each proposal. This process significantly speeds up the object detection pipeline by reducing the number of regions that need further analysis.