Classically, visual processing is described as a cascade of local feedforward computations.
Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such …

Abstract Feedforward Convolutional Neural Networks (ffCNNs) have become state-of-the-art
models both in computer vision and neuroscience. However, human-like performance of …

In crowding, perception of an object deteriorates in the presence of nearby elements.
Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation …

Investigations of visual crowding, where a target is difficult to identify because of flanking
elements, has largely used a theoretical perspective based on local interactions where …

Although we perceive a richly detailed visual world, our ability to identify individual objects is
severely limited in clutter, particularly in peripheral vision. Models of such “crowding” have …

Abstract Objects in clutter are difficult to recognize, a phenomenon known as crowding.
There is little consensus on the underlying mechanisms of crowding, and a large number of …

Visual clutter affects our ability to see. Objects that would be identifiable on their own may
become unrecognizable when presented close together (“crowding”), but the …

Crowding occurs when the presence of nearby features causes highly visible objects to
become unrecognizable. Although crowding has implications for many everyday tasks and …

Peripheral vision is fundamentally limited by the spacing between objects. When asked to
report a target's identity, observers make erroneous reports that sometimes match the …

In visual crowding, identification of a peripheral object is impaired by nearby objects. Recent
studies have demonstrated that crowding is not limited only to interaction between low-level …