AI Medical Compendium Journal:
Attention, perception & psychophysics

Showing 1 to 5 of 5 articles

CNN-based search model fails to account for human attention guidance by simple visual features.

Attention, perception & psychophysics
Recently, Zhang et al. (Nature communications, 9(1), 3730, 2018) proposed an interesting model of attention guidance that uses visual features learnt by convolutional neural networks (CNNs) for object classification. I adapted this model for search e...

Incidental auditory category learning and visuomotor sequence learning do not compete for cognitive resources.

Attention, perception & psychophysics
The environment provides multiple regularities that might be useful in guiding behavior if one was able to learn their structure. Understanding statistical learning across simultaneous regularities is important, but poorly understood. We investigate ...

Semi-supervised learning of a nonnative phonetic contrast: How much feedback is enough?

Attention, perception & psychophysics
Semi-supervised learning refers to learning that occurs when feedback about performance is provided on only a subset of training trials. Algorithms for semi-supervised learning are popular in machine learning because of their minimal reliance on labe...

Semisupervised category learning facilitates the development of automaticity.

Attention, perception & psychophysics
In the human category of learning, learning is studied in a supervised, an unsupervised, or a semisupervised way. The rare human semisupervised category of learning studies all focus on early learning. However, the impact of the semisupervised catego...

Visual properties and memorising scenes: Effects of image-space sparseness and uniformity.

Attention, perception & psychophysics
Previous studies have demonstrated that humans have a remarkable capacity to memorise a large number of scenes. The research on memorability has shown that memory performance can be predicted by the content of an image. We explored how remembering an...