Normalization techniques deep learning von huang (9 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer Nature Switzerland Ag, 2026

    3032199905 / 9783032199904

    • Hardcover

    Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books

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    Zustand: Neu

    EUR 54,93

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    Hardcover. Zustand: Brand New. second edition 2026 edition. 178 pages. 6.81x0.63x9.69 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 2023

    3031145976 / 9783031145971

    • Softcover

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    Zustand: New. In English.

  • Sprache: Englisch

    Verlag: Springer Jul 2026, 2026

    3032199905 / 9783032199904

    • Hardcover

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    Buch. Zustand: Neu. Neuware - This book surveys normalization techniques with a deep analysis in training deep neural networks. 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. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs. This Second Edition builds upon the original material with the addition of more recent proposed methods and expanded technical details for new normalization methods and network architectures tailored to specific tasks.

  • Sprache: Englisch

    Verlag: Springer-Verlag Gmbh Jul 2026, 2026

    3032199905 / 9783032199904

    • Hardcover

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    Buch. Zustand: Neu. Neuware -This book surveys normalization techniques with a deep analysis in training deep neural networks. 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. The book also serves as a resource researchers, engineers, and students who are new to the field and need to understand and train DNNs. This Second Edition builds upon the original material with the addition of more recent proposed methods and expanded technical details for new normalization methods and network architectures tailored to specific tasks.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 167 pp. Englisch.

  • Sprache: Englisch

    Verlag: Springer, 2026

    3032199905 / 9783032199904

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    Buch. Zustand: Neu. Normalization Techniques in Deep Learning | Lei Huang | Buch | Synthesis Lectures on Computer Vision | xi | Englisch | 2026 | Springer | EAN 9783032199904 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: Springer Okt 2023, 2023

    3031145976 / 9783031145971

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Taschenbuch. Zustand: Neu. Neuware - 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

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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

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    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.

  • Sprache: Englisch

    Verlag: Springer, 2023

    3031145976 / 9783031145971

    • Softcover

    Anbieter: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, DeutschlandBUCHSERVICE / ANTIQUARIAT Lars Lutzer

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    Zustand: Gebraucht - Gut

    EUR 189,00

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    Softcover. Zustand: gut. 2023. Normalization Techniques in Deep Learning In deutscher Sprache. pages.