# How does YOLO handle non-class objects?

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?

The class value will be used, only when confidence is high.