ISBN: 9783031145971 - normalization techniques in deep learning (synthesis lectures on computer vision) (2 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2023

    3031145976 / 9783031145971

    • Softcover

    Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

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    Zustand: Gebraucht - Sehr gut

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    Aktueller Preis: EUR 47,01

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    Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | ¿This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and have become basic components in most state-of-the-art DNN architectures. The author provides guidelines for elaborating, understanding, and applying normalization methods. This book is ideal for readers working on the development of novel deep learning algorithms and/or their applications to solve practical problems in computer vision and machine learning tasks. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs.…

  • Sprache: Englisch

    Verlag: Springer, 2023

    3031145976 / 9783031145971

    • Softcover

    Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

    Verkäufer/-in mit 5 Sternen
    Verkäufer/-in kontaktieren

    Zustand: Gebraucht

    Sonderangebot

    Aktueller Preis: EUR 48,42

    EUR 105,00 Versand 
    Versand von Deutschland nach USA

    Anzahl: 2 verfügbar

    Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | ¿This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to specific tasks. Normalization methods can improve the training stability, optimization efficiency, and generalization ability of deep neural networks (DNNs) and have become basic components in most state-of-the-art DNN architectures. The author provides guidelines for elaborating, understanding, and applying normalization methods. This book is ideal for readers working on the development of novel deep learning algorithms and/or their applications to solve practical problems in computer vision and machine learning tasks. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs.…