R-CNN

2000년 도입 · 논문 34편에서 사용

R-CNN, or Regions with CNN Features, is an object detection model that uses high-capacity CNNs to bottom-up region proposals in order to localize and segment objects. It uses selective search to identify a number of bounding-box object region candidates (“regions of interest”), and then extracts features from each region independently for classification.

출처: Rich feature hierarchies for accurate object detection and semantic segmentation

소개 논문: Rich feature hierarchies for accurate object detection and semantic segmentation