Fast R-CNN

Fast R-CNN is a machine learning method used to identify and locate objects within images efficiently. It processes an image once, extracting features, and then analyzes these features to predict object boundaries and categories simultaneously. This approach improves speed and accuracy compared to earlier techniques, as it shares computations across different object proposals, reducing redundancy. Fast R-CNN is commonly used in applications like image search, surveillance, and autonomous vehicles, enabling systems to detect multiple objects accurately with faster processing times.