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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Image Processing, Computer Vision, Pattern Recognition, and Graphics, 8408
Release date:	May 2014
First published:	2014
Editors:	Jia Li • Wen Gao
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
Categories:	Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Computing & IT > Applications of computing > Image processing > General
LSN:	3-319-05641-7
Barcode:	9783319056418

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