On February 21st, 2024, Chien-Yao Wang, I-Hau Yeh, and Hong-Yuan Mark Liao released the “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information'' paper, which introduces a new computer vision model architecture: YOLOv9. Later, the source code was made available, allowing anyone to train their own YOLOv9 models.
According to the YOLOv9 research team, the model architecture achieves a higher mAP than existing popular YOLO models such as YOLOv8, YOLOv7, and YOLOv5, when benchmarked against the MS COCO dataset.
YOLOv9 supports the following task types: