YOLOv2

2000년 도입 · 논문 55편에서 사용

YOLOv2, or YOLO9000, is a single-stage real-time object detection model. It improves upon YOLOv1 in several ways, including the use of Darknet-19 as a backbone, batch normalization, use of a high-resolution classifier, and the use of anchor boxes to predict bounding boxes, and more.

출처: YOLO9000: Better, Faster, Stronger

소개 논문: YOLO9000: Better, Faster, Stronger