faster rcnn

Faster R-CNN (Region-based Convolutional Neural Network) is a popular object detection algorithm in computer vision. It was introduced by Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun in their 2015 paper "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks".

Faster R-CNN is an extension of the earlier R-CNN and Fast R-CNN algorithms, which were also designed for object detection. It uses a two-stage process for object detection, where the first stage generates region proposals (i.e., regions of an image that might contain an object) and the second stage uses a convolutional neural network to classify these proposals as objects or background.

Faster R-CNN is widely used in various industries, including autonomous driving, surveillance, and robotics, due to its high accuracy and fast processing speed.