Mancas From Human Attention to Computational Attention

From Human Attention to Computational Attention

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A Multidisciplinary Approach

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Beschreibung

The new edition of this popular book introduces the study of attention, focusing on attention modeling, and addressing such themes as saliency models, signal detection, and different types of signals, including real-life applications. The first edition was written at a moment when the Deep Learning Neural Network (DNNs) techniques were just at their beginnings in terms of attention.  Deep learning has recently become a key factor in attention prediction on images and video, and attention mechanisms have become key factors in deep learning models. The second edition tackles the arrival of DNNs for attention computing in images and video, and also discusses the attention mechanisms within DNNs (attention modules, transformers, grad-cam-based saliency maps, etc.).  From Human Attention to Computational Attention 2nd Edition  also explores the parallels between the brain structures and the DNN architectures to reveal how biomimetics can improve the model designs. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering, and computer science.

The new edition of this popular book introduces the study of attention, focusing on attention modeling, and addressing such themes as saliency models, signal detection, and different types of signals, including real-life applications. The first edition was written at a moment when the Deep Learning Neural Network (DNNs) techniques were just at their beginnings in terms of attention.  Deep learning has recently become a key factor in attention prediction on images and video, and attention mechanisms have become key factors in deep learning models. The second edition tackles the arrival of DNNs for attention computing in images and video, and also discusses the attention mechanisms within DNNs (attention modules, transformers, grad-cam-based saliency maps, etc.).  From Human Attention to Computational Attention 2nd Edition  also explores the parallels between the brain structures and the DNN architectures to reveal how biomimetics can improve the model designs. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering, and computer science.

 


Enables readers to access attention modeling work across disciplines and communities Balances work on theory and practical applications in order to deepen understanding of attention Explores Deep Learning Neural Networks for attention computing

Autor*in

Matei Mancas

Themen in »From Human Attention to Computational Attention«

Attention Modeling Saliency Models Brain Attention Signal Detection Attention Applications Neural Networks Deep Learning Neural Networks Biomimetics

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Details

ISBN: 9783031842993
Verlag: Springer International Publishing
Erscheinung: 16.07.2025

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