Human attention computational multidisciplinary (4 résultats)

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  • Langue : anglais

    Edité par Springer, 2025

    3031842995 / 9783031842993

    • Couverture rigide

    Vendeur : California Books, Miami, FL, Etats-UnisCalifornia Books

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    Etat: Neuf

    EUR 251,82

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    Expédition nationale : Etats-Unis

    Quantité disponible : Plus de 20 disponibles

    Etat : New.

  • Langue : anglais

    Edité par Springer, 2026

    3031843029 / 9783031843020

    • Couverture souple

    Vendeur : preigu, Osnabrück, Allemagnepreigu

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    Etat: Neuf

    EUR 184,95

    EUR 70,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 5 disponible(s)

    Taschenbuch. Etat : Neu. From Human Attention to Computational Attention | A Multidisciplinary Approach | Matei Mancas (u. a.) | Taschenbuch | viii | Englisch | 2026 | Springer | EAN 9783031843020 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Langue : anglais

    Edité par Springer, 2026

    3031843029 / 9783031843020

    • Couverture souple

    Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH

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    Etat: Neuf

    EUR 230,55

    EUR 35,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 1 disponible(s)

    Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 bookis truly multi-disciplinary, collating work from psychology, neuroscience, engineering, and computer science.…

  • Langue : anglais

    Edité par Springer, 2025

    3031842995 / 9783031842993

    • Couverture rigide

    Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH

    Vendeur avec une évaluation de 5 étoiles
    Contacter le vendeur

    Etat: Neuf

    EUR 230,55

    EUR 35,00 expédition 
    Expédition depuis Allemagne vers Etats-Unis

    Quantité disponible : 1 disponible(s)

    Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 bookis truly multi-disciplinary, collating work from psychology, neuroscience, engineering, and computer science.…