One Way Human Vision Is Better Than a Machine’s
The problem machine vision has with understanding what things *should* look like creates risks for traffic video safety systems, researchers sayBecause machine vision absorbs information without context, it simply doesn’t “see” what a human sees — and the results could be “dangerous in real-world AI applications,” warns York University prof James Elder. He and his colleagues did an interesting experiment with deep convolutional neural networks (DCNNs). They used “Frankensteins” — models of life forms that are distorted in some way — to determine how they would be interpreted by humans or by machine vision: “Frankensteins are simply objects that have been taken apart and put back together the wrong way around,” says Elder. “As a result, they have all the right local features, but in the wrong places.” The investigators found that while the human visual system is confused by Read More ›
