I have been reading more about computer vision and I'm bothered by YOLO and similar deep learning architectures.
The thing I am confused about is how non-class image sections are dealt with. In particular, it's not clear to me at all why YOLO doesn't consider every part of an image a possible class.
What actually sets the cutoff for detection and then classification?