| 書(shū)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video | http://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(shū)名稱 | Springer Series in Cognitive and Neural Systems |
| 圖書(shū)封面 |  |
| 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 |
| doi | https://doi.org/10.1007/978-1-4939-3435-5 |
| isbn_softcover | 978-1-4939-8050-5 |
| isbn_ebook | 978-1-4939-3435-5Series ISSN 2363-9105 Series E-ISSN 2363-9113 |
| issn_series | 2363-9105 |
| copyright | Springer Science+Business Media New York 2016 |
|Archiver|手機(jī)版|小黑屋|
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