Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to
model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have …

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

A few years ago, the first CNN surpassed human performance on ImageNet. However, it
soon became clear that machines lack robustness on more challenging test cases, a major …

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

Natural and artificial audition can in principle acquire different solutions to a given problem.
The constraints of the task, however, can nudge the cognitive science and engineering of …

Line drawings convey meaning with just a few strokes. Despite strong simplifications,
humans can recognize objects depicted in such abstracted images without effort. To what …

Convolutional neural networks (CNNs) are one of the most successful computer vision
systems to solve object recognition. Furthermore, CNNs have major applications in …

On several key issues we agree with the commentators. Perhaps most importantly, everyone
seems to agree that psychology has an important role to play in building better models of …

Biological nervous systems constitute important sources of inspiration towards computers
that are faster, cheaper, and more energy efficient. Neuromorphic disciplines view the brain …

Convolutional neural networks (CNNs) are often described as promising models of human
vision, yet they show many differences from human abilities. We focus on a superhuman …