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Evolution of YOLO in Computer Vision
The chapter explores the development of YOLO models in computer vision, comparing past iterations like YOLO 2 and fast R-CNN to the latest YOLOv9. It highlights the advancements in neural network architecture and training methods, emphasizing YOLO's effectiveness in real-time object detection. Additionally, it discusses the enhancements in YOLOv9, focusing on efficiency, licensing, and the integration of reversible functions to improve information flow within the network.