Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …

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 …

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

Similarity and categorization are fundamental processes in human cognition that help
complex organisms make sense of the cacophony of information in their environment. These …

Models that predict brain responses to stimuli provide one measure of understanding of a
sensory system and have many potential applications in science and engineering. Deep …

Artificial neural networks (ANNs) have emerged as an essential tool in machine learning,
achieving remarkable success across diverse domains, including image and speech …

Abstract 3D visual grounding aims to locate the referred target object in 3D point cloud
scenes according to a free-form language description. Previous methods mostly follow a two …

Facial recognition errors can jeopardize national security, criminal justice, public safety and
civil rights. Here, we compare the most accurate humans and facial recognition technology …

Inferences made about objects via vision, such as rapid and accurate categorization, are
core to primate cognition despite the algorithmic challenge posed by varying viewpoints and …