Join our mailing list
Get exclusive deals and learn about new products!
Reliable shipping
Flexible returns
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.
Published by: Springer
Publication Date: 2023-02-03
Format: Hardcover
ISBN-13: 9789811985690
DOI: 10.1007/978-981-19-8570-6
Dimensions: 235cm x155cm
Pages: 221