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Visual Saliency Computation: A Machine Learning Perspective (Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Graphics)
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Description for Visual Saliency Computation: A Machine Learning Perspective (Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Graphics)
Paperback. Visual Saliency Computation Editor(s): Li, Jia; Gao, Wen. Series: Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Graphics. Num Pages: 252 pages, 100 black & white illustrations, biography. BIC Classification: UNF; UYQ; UYT. Category: (P) Professional & Vocational. Dimension: 235 x 175 x 15. Weight in Grams: 388.
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 ... Read more
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 ... Read more
Product Details
Format
Paperback
Publication date
2014
Publisher
Springer
Condition
New
Series
Lecture Notes in Computer Science / Image Processing, Computer Vision, Pattern Recognition, and Gra
Number of Pages
240
Place of Publication
Cham, Switzerland
ISBN
9783319056418
SKU
V9783319056418
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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