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From Human Attention to Computational Attention

Matei Mancas - Personal Name; Vincent P. Ferrera - Personal Name; Nicolas Riche - Personal Name; John G. Taylor - Personal Name;

This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. It introduces the study of attention and focuses on attention modeling, addressing such themes as saliency models, signal detection and different types of signals, as well as real-life applications. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering and computer science, amongst other disciplines.

What is attention? We all pay attention every single moment of our lives. Attention is how the brain selects and prioritizes information. The study of attention has become incredibly complex and divided: this timely volume assists the reader by drawing together work on the computational aspects of attention from across the disciplines. Those working in the field as engineers will benefit from this book’s introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention. The work features practical reviews and chapters that are quick and easy to read, as well as chapters which present deeper, more complex knowledge. Everyone whose work relates to human perception, to image, audio and video processing will find something of value

in this book, from students to researchers and those in industry.


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Detail Information
Series Title
Springer Series in Cognitive and Neural Systems
Call Number
-
Publisher
New York : Springer., 2016
Collation
-
Language
English
ISBN/ISSN
978-1-4939-3435-5
Classification
NONE
Content Type
-
Media Type
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Carrier Type
-
Edition
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Subject(s)
-
Specific Detail Info
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Statement of Responsibility
Matei Mancas, Vincent P. Ferrera, Nicolas Riche, John G. Taylor
Other Information
Cataloger
Jemadi
Source
-
Validator
Jemadi
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-1-4939-3435-5
Journal Volume
-
Journal Issue
-
Subtitle
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  • From Human Attention to Computational Attention
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