Object detection is an advanced form of image classification where a neural network predicts objectsin an image and points them out in the form of bounding boxes. Compared to the approach taken by object detection algorithms before YOLO, which repurpose classifiers to perform detection, YOLO proposes the use of an end-to-end neural network that makes predictions of bounding boxes and class probabilities all at once.