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

Semantic representations in higher sensory cortices form the basis for robust, yet flexible
behavior. These representations are acquired over the course of development in an …

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

Biological and artificial information processing systems form representations that they can
use to categorize, reason, plan, navigate, and make decisions. How can we measure the …

Young children develop sophisticated internal models of the world based on their visual
experience. Can such models be learned from a child's visual experience without strong …

As children grow older, they develop an intuitive understanding of the physical processes
around them. Their physical understanding develops in stages, moving along …

Humans outperform object recognizers despite the fact that models perform well on current
datasets, including those explicitly designed to challenge machines with debiased images …

Object recognition is the process by which humans organize the visual world into
meaningful perceptual units. In this Review, we examine the developmental origins and …

Standardized reporting of data is crucial for out-of-hospital cardiac arrest (OHCA) research.
While the implementation of first responder systems dispatching volunteers to OHCA is …

Human-AI complementarity is important when neither the algorithm nor the human yields
dominant performance across all instances in a given context. Recent work that explored …