What is YOLO architecture in object detection?
Updated May 15, 2026
Short answer
YOLO is a real-time object detection model that predicts bounding boxes and classes in one pass.
Deep explanation
YOLO (You Only Look Once) divides images into grids and predicts bounding boxes, confidence scores, and class probabilities simultaneously using a single CNN. It is extremely fast compared to region proposal-based methods.
Real-world example
Used in surveillance systems for real-time person detection.
Common mistakes
- Assuming YOLO uses region proposals like Faster R-CNN.
Follow-up questions
- How does YOLO handle multiple objects?
- What makes YOLO fast?