Visual Saliency Computation - A Machine Learning Perspective (Paperback, 2014 ed.)


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.

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Product Description

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.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

Image Processing, Computer Vision, Pattern Recognition, and Graphics, 8408

Release date

May 2014

Availability

Expected to ship within 10 - 15 working days

First published

2014

Editors

,

Dimensions

235 x 155 x 15mm (L x W x T)

Format

Paperback

Pages

240

Edition

2014 ed.

ISBN-13

978-3-319-05641-8

Barcode

9783319056418

Categories

LSN

3-319-05641-7



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