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Titlebook: From Human Attention to Computational Attention; A Multidisciplinary Matei Mancas,Vincent P. Ferrera,John G. Taylor Book 2016 Springer Sci

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書目名稱From Human Attention to Computational Attention
副標(biāo)題A Multidisciplinary
編輯Matei Mancas,Vincent P. Ferrera,John G. Taylor
視頻videohttp://file.papertrans.cn/349/348722/348722.mp4
概述Enables readers to access attention modeling work across the disciplines and communities.Balances work on theory and practical applications in order to deepen understanding of attention.Supports commu
叢書名稱Springer Series in Cognitive and Neural Systems
圖書封面Titlebook: From Human Attention to Computational Attention; A Multidisciplinary  Matei Mancas,Vincent P. Ferrera,John G. Taylor Book 2016 Springer Sci
描述.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 hu
出版日期Book 2016
關(guān)鍵詞Attention Modeling; Saliency Models; Brain Attention; Signal Detection; Attention Applications; Image, Vi
版次1
doihttps://doi.org/10.1007/978-1-4939-3435-5
isbn_softcover978-1-4939-8050-5
isbn_ebook978-1-4939-3435-5Series ISSN 2363-9105 Series E-ISSN 2363-9113
issn_series 2363-9105
copyrightSpringer Science+Business Media New York 2016
The information of publication is updating

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