Assessing Shape Bias Property of Convolutional Neural Networks

Understand

It is known that humans display "shape bias" when classifying new items, i.e., they prefer to categorize objects based on their shape rather than color.

• Convolutional Neural Networks (CNNs) are also designed to take into account the spatial structure of image data.
• In fact, experiments on image datasets, consisting of triples of a probe image, a shape-match and a color-match, have shown that one-shot learning models display shape bias as well.
• In this paper, we examine the shape bias property of CNNs.