Librería: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Reino Unido
EUR 18,02
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: 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.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 58,78
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In English.
Librería: Chiron Media, Wallingford, Reino Unido
EUR 55,46
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 59,99
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 59,99
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 71,03
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 77,37
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. pp. XIII, 212 86 illus., 67 illus. in color. 1 Edition NO-PA16APR2015-KAP.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 72,08
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 98,10
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Librería: The Book Corner, Beaverton, OR, Estados Unidos de America
EUR 108,46
Cantidad disponible: 1 disponibles
Añadir al carritohardcover. Condición: 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.
EUR 38,98
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: 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.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 162,73
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 162,73
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 162,72
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 179,40
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 180,39
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 160,60
Cantidad disponible: 1 disponibles
Añadir al carritopaperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 181,14
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 202,12
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 211,64
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
EUR 140,00
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Springer Nature Switzerland, 2018
ISBN 10: 3319863835 ISBN 13: 9783319863832
Librería: preigu, Osnabrück, Alemania
EUR 140,00
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Domain Adaptation in Computer Vision Applications | Gabriela Csurka | Taschenbuch | x | Englisch | 2018 | Springer Nature Switzerland | EAN 9783319863832 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 214,03
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. pp. 317.
Idioma: Inglés
Publicado por Springer International Publishing, 2021
ISBN 10: 3030455319 ISBN 13: 9783030455316
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Springer International Publishing, 2018
ISBN 10: 3319863835 ISBN 13: 9783319863832
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030455289 ISBN 13: 9783030455286
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Springer International Publishing, 2017
ISBN 10: 3319583468 ISBN 13: 9783319583464
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2021
ISBN 10: 3030455319 ISBN 13: 9783030455316
Librería: Revaluation Books, Exeter, Reino Unido
EUR 228,82
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 267 pages. 9.25x6.10x0.63 inches. In Stock.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 230,76
Cantidad disponible: 2 disponibles
Añadir al carritoHardcover. Condición: Brand New. 267 pages. 9.25x6.10x0.75 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 228,41
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.