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Visual Saliency Computation / A Machine Learning Perspective / Wen Gao (u. a.) / Taschenbuch / Image Processing, Computer Vision, Pattern Recognition, and Graphics / Paperback / Englisch / 2014 - Gao, Wen
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Gao, Wen:

Visual Saliency Computation / A Machine Learning Perspective / Wen Gao (u. a.) / Taschenbuch / Image Processing, Computer Vision, Pattern Recognition, and Graphics / Paperback / Englisch / 2014 - Pasta blanda

2014, ISBN: 9783319056418

[ED: Taschenbuch], [PU: Springer International Publishing], This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdiscip… Más…

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Visual Saliency Computation A Machine Learning Perspective Wen Gao (u. a.) Taschenbuch Image Processing, Computer Vision, Pattern Recognition, and Graphics Paperback Englisch 2014 - Gao, Wen
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Gao, Wen:

Visual Saliency Computation A Machine Learning Perspective Wen Gao (u. a.) Taschenbuch Image Processing, Computer Vision, Pattern Recognition, and Graphics Paperback Englisch 2014 - Pasta blanda

2014, ISBN: 9783319056418

[ED: Taschenbuch], [PU: Springer International Publishing], This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdiscip… Más…

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Visual Saliency Computation
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Visual Saliency Computation - libro nuevo

ISBN: 9783319056418

This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in… Más…

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Li, Jia und Wen Gao:
Visual Saliency Computation A Machine Learning Perspective 2014 - libro usado

2014, ISBN: 9783319056418

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Visual Saliency Computation A Machine Learning Perspective - Li, Jia und Wen Gao
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Li, Jia und Wen Gao:
Visual Saliency Computation A Machine Learning Perspective - libro usado

2014, ISBN: 9783319056418

[PU: Springer International Publishing], Buchschnitt verkürzt - gepflegter, sauberer Zustand - Ausgabejahr 2014 24691926/12, DE, [SC: 0.00], gebraucht; sehr gut, gewerbliches Angebot, 201… Más…

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Detalles del libro
Visual Saliency Computation
Autor:
Título:
ISBN:

9783319056418


This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book from an innovative perspective that combines both neurobiology and machine learning. The book is also well-structured to address a wide range of readers, from specialists in the field to general readers interested in computer science and cognitive psychology. With this book, a reader can start from the very basic question of "what is visual saliency?" and progressively explore the problems in detecting salient locations, extracting salient objects, learning prior knowledge, evaluating performance, and using saliency in real-world applications. It is highly expected that this book will spark a great interest of research in the related communities in years to come.

Detalles del libro - Visual Saliency Computation


EAN (ISBN-13): 9783319056418
ISBN (ISBN-10): 3319056417
Tapa dura
Tapa blanda
Año de publicación: 2014
Editorial: Springer International Publishing

Libro en la base de datos desde 2014-04-01T21:25:16-06:00 (Mexico City)
Página de detalles modificada por última vez el 2024-01-16T16:59:05-06:00 (Mexico City)
ISBN/EAN: 9783319056418

ISBN - escritura alterna:
3-319-05641-7, 978-3-319-05641-8
Mode alterno de escritura y términos de búsqueda relacionados:
Autor del libro: wen, gao, gào
Título del libro: learning processing, inglés visual, computer image, lecture notes computer science, computer perspective, pattern recognition and machine learning, computer vision graphics, jia, learning englisch, wen

Datos del la editorial

Autor: Jia Li; Wen Gao
Título: Lecture Notes in Computer Science; Image Processing, Computer Vision, Pattern Recognition, and Graphics; Visual Saliency Computation - A Machine Learning Perspective
Editorial: Springer; Springer International Publishing
240 Páginas
Año de publicación: 2014-05-15
Cham; CH
Impreso en
Idioma: Inglés
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XII, 240 p. 100 illus.

BC; Hardcover, Softcover / Informatik, EDV/Anwendungs-Software; Maschinelles Sehen, Bildverstehen; Verstehen; artificial intelligence; benchmarks; computer vision; human cognition; human vision; image processing; information processing; machine learning; neurobiology; performance evaluation; saliency detection; salient objects; salient region detections; video processing; visual attention; visual saliency computation; Computer Vision; Artificial Intelligence; Data Mining and Knowledge Discovery; Künstliche Intelligenz; Data Mining; Wissensbasierte Systeme, Expertensysteme; EA

This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book from an innovative perspective that combines both neurobiology and machine learning. The book is also well-structured to address a wide range of readers, from specialists in the field to general readers interested in computer science and cognitive psychology. With this book, a reader can start from the very basic question of "what is visual saliency?" and progressively explore the problems in detecting salient locations, extracting salient objects, learning prior knowledge, evaluating performance, and using saliency in real-world applications. It is highly expected that this book will spark a great interest of research in the related communities in years to come.
Written to be easily understood by a wide range of readers, from specialists in the field of visual saliency computation to general readers interested in computer science and cognitive psychology Offers a foreword by Zhengyou Zhang, included in the front matter and is freely available for perusal on SpringerLink Introduces concepts step-by-step, starting from visual saliency and progressively exploring the problems in modeling saliency, extracting salient objects, mining prior knowledge, evaluating performance, and using saliency in real-world applications

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