"You Only Look Once: Unified, Real-Time Object Detection", introduces YOLO, a novel approach to object detection. This method frames object detection as a regression problem, allowing a single neural network to predict bounding boxes and associated class probabilities directly from full images in a single evaluation. YOLO is incredibly fast, processing images at 45 frames per second, making it suitable for real-time applications. Compared to existing systems, YOLO exhibits a lower rate of false positives and demonstrates strong generalization to new domains, making it highly suitable for applications such as self-driving cars and assistive devices.