What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective

What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective

Selective attention plays an essential role in information acquisition and utilization from the environment. In the past 50 years, research on selective attention has been a central topic in cognitive science. Compared with unimodal studies, crossmodal studies are more complex but necessary to solve...

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Bibliographic Details
Main Authors: Di Fu, Cornelius Weber, Guochun Yang, Matthias Kerzel, Weizhi Nan, Pablo Barros, Haiyan Wu, Xun Liu, Stefan Wermter
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-02-01
Series:Frontiers in Integrative Neuroscience
Subjects:
selective attention
visual attention
auditory attention
crossmodal learning
computational modeling
deep learning
Online Access:https://www.frontiersin.org/article/10.3389/fnint.2020.00010/full

Internet

https://www.frontiersin.org/article/10.3389/fnint.2020.00010/full

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