Venkateswara hemanth (26 risultati)

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  • Lingua: Inglese

    Editore: Palgrave Macmillan, 2020

    3030455289 / 9783030455286

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    Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 268 | Sprache: Englisch | Produktart: Bücher | This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.…

  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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  • Lingua: Inglese

    Editore: Springer, 2020

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  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2021

    3030455319 / 9783030455316

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  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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  • Lingua: Inglese

    Editore: Birkhäuser, 2021

    3030455319 / 9783030455316

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

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.…

  • Lingua: Inglese

    Editore: Birkhäuser, 2020

    3030455289 / 9783030455286

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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 - This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.…

  • Lingua: Inglese

    Editore: Springer, 2021

    3030455319 / 9783030455316

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    Taschenbuch. Condizione: Neu. Domain Adaptation in Computer Vision with Deep Learning | Hemanth Venkateswara (u. a.) | Taschenbuch | xi | Englisch | 2021 | Springer | EAN 9783030455316 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Lingua: Inglese

    Editore: Springer, 2021

    3030455319 / 9783030455316

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    Da: Books Puddle, Woodside, NY, U.S.A.Books Puddle

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    Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.

  • Lingua: Inglese

    Editore: Springer-Nature New York Inc, 2021

    3030455319 / 9783030455316

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    Paperback. Condizione: Brand New. 267 pages. 9.25x6.10x0.63 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2020

    3030455289 / 9783030455286

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    Hardcover. Condizione: Brand New. 267 pages. 9.25x6.10x0.75 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2021

    3030455319 / 9783030455316

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  • Lingua: Inglese

    Editore: Springer, 2020

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  • Lingua: Inglese

    Editore: Springer International Publishing Aug 2020, 2020

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

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book. 268 pp. Englisch.…

  • Lingua: Inglese

    Editore: Springer, Berlin|Springer International Publishing|Springer, 2021

    3030455319 / 9783030455316

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    Da: moluna, Greven, Germaniamoluna

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to.…

  • Lingua: Inglese

    Editore: Springer International Publishing, 2020

    3030455289 / 9783030455286

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    Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A one-stop-shop for domain adaptation research that highlights the various approaches to domain adaptationRevisits the problem statement and assumptions in domain adaptationProposes promising directions for future research in .…

  • Lingua: Inglese

    Editore: Springer International Publishing Aug 2021, 2021

    3030455319 / 9783030455316

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

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book. 268 pp. Englisch.…

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    Editore: Springer, 2020

    3030455289 / 9783030455286

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  • Lingua: Inglese

    Editore: Springer, Springer International Publishing Aug 2021, 2021

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 268 pp. Englisch. …

  • Lingua: Inglese

    Editore: Springer, Springer International Publishing Aug 2020, 2020

    3030455289 / 9783030455286

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    Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation.Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation.This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 268 pp. Englisch.…

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    Editore: Springer, 2021

    3030455319 / 9783030455316

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: Springer, 2021

    3030455319 / 9783030455316

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