Description |
1 online resource (xiv, 221 pages) : illustrations (chiefly color), |
Series |
Studies in computational intelligence, 1860-9503 ; volume 1082 |
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Studies in computational intelligence ; volume 1082. 1860-9503
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Contents |
Introduction -- Survey of Image Co-segmentation -- Mathematical Background -- Co-segmentation using a Classification Framework -- Use of Maximum Common Subgraph Matching -- Maximally Occurring Common Subgraph Matching -- Co-segmentation using Graph Convolutional Neural Network -- Use of a Conditional Siamese Convolutional Network -- Few-shot Learning for Co-segmentation -- Conclusions |
Summary |
This book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder-decoder network, meta-learning, conditional variational encoder-decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning |
Bibliography |
Includes bibliographical references |
Notes |
Online resource; title from PDF title page (SpringerLink, viewed February 6, 2023) |
Subject |
Image segmentation.
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Image segmentation
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Genre/Form |
Electronic books
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Form |
Electronic book
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Author |
Velmurugan, Rajbabu, author.
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|
Banerjee, Sayan, author
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Chaudhuri, Subhasis, author.
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ISBN |
9789811985706 |
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9811985707 |
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