YOLO (You Only Look Once)

YOLO (You Only Look Once) is a series of real-time object detection algorithms that utilize convolutional neural networks to detect and classify multiple objects within an image or video frame in a single evaluation. Introduced by Joseph Redmon et al. in 2015, YOLO reframes object detection as a single regression problem, significantly enhancing detection speed and accuracy compared to traditional methods. Over successive versions, YOLO has evolved to improve performance, efficiency, and adaptability, becoming a cornerstone in computer vision applications such as autonomous driving, surveillance, and robotics.