Machine vision that sees things more the way we do is easier for us to understand

A new image recognition algorithm uses the way humans see things for inspiration. The context: When humans look at a new image of something, we identify what it is based on a collection of recognizable features. We might identify the species of a bird, for example, by the contour of its beak, the colors of its plume, and the shape of its feet. A neural network, however, simply looks for pixel patterns across the entire image without discriminating between the actual bird and its background. This makes the neural network more vulnerable to mistakes and makes it harder for humans to diagnose them.