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Añadir al carritoCondición: New. pp. 258 1st ed. 2019 edition NO-PA16APR2015-KAP.
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Publicado por Springer-Nature New York Inc, 2020
ISBN 10: 3030137759 ISBN 13: 9783030137755
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ISBN 10: 3030137759 ISBN 13: 9783030137755
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
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Añadir al carritoTaschenbuch. Condición: Neu. Image Texture Analysis | Foundations, Models and Algorithms | Chih-Cheng Hung (u. a.) | Taschenbuch | xii | Englisch | 2020 | Springer | EAN 9783030137755 | 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 International Publishing, Springer International Publishing, 2019
ISBN 10: 3030137724 ISBN 13: 9783030137724
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
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Publicado por Springer International Publishing Okt 2020, 2020
ISBN 10: 3030137759 ISBN 13: 9783030137755
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work. 272 pp. Englisch.
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Paulo Chih-Hsing Wu Rong-Sen YangRong-Sen Yang, MD, PhDDirector and Professor, Orthopaedic Surgery, College of Medicine, National Taiwan University & Hospital, Taipei, Taiwan.Fragility fractures are common among the patients with.
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Añadir al carritoCondición: New. Print on Demand pp. 258.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 258.
Idioma: Inglés
Publicado por Springer International Publishing Jun 2019, 2019
ISBN 10: 3030137724 ISBN 13: 9783030137724
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work. 272 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030137759 ISBN 13: 9783030137755
Librería: moluna, Greven, Alemania
EUR 44,67
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews the state of the art in models and algorithms for texture analysis, including deep learning and image texture analysisIntroduces the K-View model and its advanced models, highlighting the benefits offered by these modelsDiscusses the t.
Librería: Majestic Books, Hounslow, Reino Unido
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Idioma: Inglés
Publicado por Springer International Publishing, 2019
ISBN 10: 3030137724 ISBN 13: 9783030137724
Librería: moluna, Greven, Alemania
EUR 60,06
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews the state of the art in models and algorithms for texture analysis, including deep learning and image texture analysisIntroduces the K-View model and its advanced models, highlighting the benefits offered by these modelsDiscusses the t.
Idioma: Inglés
Publicado por Springer, Birkhäuser Okt 2020, 2020
ISBN 10: 3030137759 ISBN 13: 9783030137755
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 272 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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