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Image Co-Segmentation (2023)

Contributor(s): Hati, Avik (Author), Velmurugan, Rajbabu (Author), Banerjee, Sayan (Author), Chaudhuri, Subhasis (Author)

ISBN: 9789811985720

Publisher: Springer

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Pub Date: February 3, 2024

Lexile Code: 0000

Features: Illustrated

Target Age Group: NA to NA

Physical Info: 0.50" H x 9.21" L x 6.14" W ( 0.74 lbs) 221 pages

Series: Studies in Computational Intelligence

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Description:

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.

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