faster rcnn

Faster R-CNN is a deep learning algorithm for object detection. It was introduced by Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun in 2015. Faster R-CNN builds on the previous Region-CNN (R-CNN) and Fast R-CNN algorithms, and improves the speed and accuracy of object detection.

The key innovation of Faster R-CNN is the introduction of a Region Proposal Network (RPN) that shares convolutional features with the detection network. The RPN generates region proposals, which are then fed into the detection network to classify and refine the object detections. This approach allows for end-to-end training of the entire system and significantly improves the speed and accuracy of object detection.

Faster R-CNN has been widely used in various applications such as autonomous vehicles, surveillance, and robotics.