What does "YOLO11" mean?

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YOLO11 is a model used in computer vision to detect and identify objects in images and videos. It's known for its speed and accuracy, making it great for real-time applications. Unlike older methods that process images in parts, YOLO11 looks at the whole image at once, which helps it find multiple objects quickly.

In traffic surveillance, YOLO11 can spot small objects like pedestrians and cyclists, even when they are hard to see or partially blocked. This is important for improving safety on the roads and aiding decision-making in smart transportation systems.

In agriculture, YOLO11 is also used to identify and outline objects like apples in orchards. By using advanced techniques, it can create and label images without needing a lot of physical data collection or manual work. This makes it easier and faster to develop accurate models for various applications.

Overall, YOLO11 plays a vital role in different fields, helping to improve efficiency and accuracy in object detection and tracking.