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![Stock image for Domain Adaptation for Visual Recognition (Foundations and Trends (R) in Computer Graphics and Vision): 25 (Foundations and Trends® in Computer Graphics and Vision) [Paperback] Gopalan, Raghuraman; Li, Ruonan and Patel, Vishal M. for sale by Hay-on-Wye Booksellers](https://pictures.abebooks.com/isbn/9781680830309-uk-300.jpg)
Domain Adaptation for Visual Recognition (Foundations and Trends (R) in Computer Graphics and Vision): 25 (Foundations and Trends® in Computer Graphics and Vision) [Paperback] Gopalan, Raghuraman; Li, Ruonan and Patel, Vishal M.
Seller: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, United Kingdom
Seller rating 5 out of 5 stars
Condition: Very Good. Minor wear at edges/corners. Faint storage scratches to cover. Minor storage marks at extremities of text blocks. Text as new and unread.
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Visual Domain Adaptation in the Deep Learning Era (Synthesis Lectures on Computer Vision)
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£ 46.62
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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning (Image Processing, Computer Vision, Pattern Recognition, and Graphics)
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data (Image Processing, Computer Vision, Pattern Recognition, and Graphics)
Book 157 of 300: Lecture Notes in Computer ScienceSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Condition: New. pp. XIII, 212 86 illus., 67 illus. in color. 1 Edition NO-PA16APR2015-KAP.
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Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health (Image Processing, Computer Vision, Pattern Recognition, and Graphics)
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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hardcover. Condition: New. Hardback. No dust jacket. Cover edges and corners in good shape. Spine is tight. Pages are clean, no markings, notes or stains. Ships from Friends bookstore to benefit Beaverton (Oregon) library.
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Condition: 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.
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Domain Adaptation in Computer Vision with Deep Learning
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Domain Adaptation in Computer Vision with Deep Learning
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Domain Adaptation in Computer Vision With Deep Learning
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paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Domain Adaptation in Computer Vision With Deep Learning
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Condition: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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Taschenbuch. Condition: Neu. Domain Adaptation in Computer Vision Applications | Gabriela Csurka | Taschenbuch | Advances in Computer Vision and Pattern Recognition | x | Englisch | 2018 | Springer | EAN 9783319863832 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Domain Adaptation in Computer Vision with Deep Learning
Language: English
Published by Springer International Publishing, 2021
ISBN 10: 3030455319 ISBN 13: 9783030455316
Taschenbuch. Condition: 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.
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Domain Adaptation in Computer Vision Applications
Book 65 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer International Publishing, 2018
ISBN 10: 3319863835 ISBN 13: 9783319863832
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes.Topics and features: surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous data as well as deep architectures; presents a positioning of the dataset bias in the CNN-based feature arena; proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data; discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models; addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection; describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning.This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning.
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Domain Adaptation in Computer Vision with Deep Learning
Language: English
Published by Springer International Publishing, 2020
ISBN 10: 3030455289 ISBN 13: 9783030455286
Buch. Condition: 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.
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Domain Adaptation in Computer Vision Applications
Book 65 of 86: Advances in Computer Vision and Pattern RecognitionLanguage: English
Published by Springer International Publishing, 2017
ISBN 10: 3319583468 ISBN 13: 9783319583464
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This comprehensive text/reference presents a broad review of diverse domain adaptation (DA) methods for machine learning, with a focus on solutions for visual applications. The book collects together solutions and perspectives proposed by an international selection of pre-eminent experts in the field, addressing not only classical image categorization, but also other computer vision tasks such as detection, segmentation and visual attributes.Topics and features: surveys the complete field of visual DA, including shallow methods designed for homogeneous and heterogeneous data as well as deep architectures; presents a positioning of the dataset bias in the CNN-based feature arena; proposes detailed analyses of popular shallow methods that addresses landmark data selection, kernel embedding, feature alignment, joint feature transformation and classifier adaptation, or the case of limited access to the source data; discusses more recent deep DA methods, including discrepancy-based adaptation networks and adversarial discriminative DA models; addresses domain adaptation problems beyond image categorization, such as a Fisher encoding adaptation for vehicle re-identification, semantic segmentation and detection trained on synthetic images, and domain generalization for semantic part detection; describes a multi-source domain generalization technique for visual attributes and a unifying framework for multi-domain and multi-task learning.This authoritative volume will be of great interest to a broad audience ranging from researchers and practitioners, to students involved in computer vision, pattern recognition and machine learning.
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Domain Adaptation in Computer Vision With Deep Learning
Language: English
Published by Springer-Nature New York Inc, 2021
ISBN 10: 3030455319 ISBN 13: 9783030455316
Paperback. Condition: Brand New. 267 pages. 9.25x6.10x0.63 inches. In Stock.
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Hardcover. Condition: Brand New. 267 pages. 9.25x6.10x0.75 inches. In Stock.
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Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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