Seonglae ChoYou Only Look Once
YOLO is a real-time framework for object detection, recognized for its optimal balance of efficiency and performance. It's essential in areas such as self-driving cars, robot navigation, and object tracking where quick and precise object recognition is crucial.
YOLO Models
YOLOv10
YOLOv10 removes the requirement for non-maximum suppression through stable dual assignments, which enhances efficiency and lessens delay. It leverages CSPNet for superior gradient flow and employs PAN layers for the fusion of features across multiple scales.
YOLOv9
YOLOv9: Learning What You Want to Learn Using Programmable...
Today's deep learning methods focus on how to design the most appropriate objective functions so that the prediction results of the model can be closest to the ground truth. Meanwhile, an...
https://arxiv.org/abs/2402.13616
