Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

Discovering the visual features and representations used by the brain to recognize objects is
a central problem in the study of vision. Recently, neural network models of visual object …

How do we recognize objects despite changes in their appearance? The past three decades
have been witness to intense debates regarding both whether objects are encoded …

Although the study of visual perception has made more progress in the past 40 years than
any other area of cognitive science, there remain major disagreements as to how closely …

Deep neural networks (DNNs) are machine learning algorithms that have revolutionized
computer vision due to their remarkable successes in tasks like object classification and …

Human visual object recognition is typically rapid and seemingly effortless, as well as largely
independent of viewpoint and object orientation. Until very recently, animate visual systems …

Recent advances in neural network modeling have enabled major strides in computer vision
and other artificial intelligence applications. Human-level visual recognition abilities are …

Convolutional neural networks (CNNs) were inspired by early findings in the study of
biological vision. They have since become successful tools in computer vision and state-of …

The many successes of deep neural networks (DNNs) over the past decade have largely
been driven by computational scale rather than insights from biological intelligence. Here …

Abstracts Cognitive science typically postulates unconscious mental phenomena,
computational or otherwise, to explain cognitive capacities. The mental phenomena in …