Isbn: 9783031842993 - from human attention to computational attention: a multidisciplinary approach (7 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2025

    3031842995 / 9783031842993

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  • Lingua: Inglese

    Editore: Springer, 2025

    3031842995 / 9783031842993

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  • Lingua: Inglese

    Editore: Springer, 2025

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Buch. Condizione: 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.…

  • Lingua: Inglese

    Editore: Springer, 2025

    3031842995 / 9783031842993

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  • Lingua: Inglese

    Editore: Springer, Berlin, Springer Nature Switzerland, Springer, 2025

    3031842995 / 9783031842993

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    EUR 213,99

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 339 pp. Englisch. …

  • Lingua: Inglese

    Editore: Springer, Springer Jul 2025, 2025

    3031842995 / 9783031842993

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 348 pp. Englisch.…

  • Lingua: Inglese

    Editore: Springer International Publishing AG, Cham, 2025

    3031842995 / 9783031842993

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    EUR 244,20

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    Hardcover. Condizione: new. Hardcover. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…