One-Stage Object Detection Models


Introduced by Redmon et al. in YOLO9000: Better, Faster, Stronger

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.

Source: YOLO9000: Better, Faster, Stronger


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