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hati image co segmentation 2023

Type:: E-books
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Size:: 9.8 MB
Uploaded On:: Feb. 5, 2023, 11:18 a.m.
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Info Hash:: 1806BFF57E9EA4A256DB995375186B7C7189D572

Textbook in PDF format 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. Introduction Survey of Image Co-segmentation Mathematical Background Maximum Common Subgraph Matching Maximally Occurring Common Subgraph Matching Co-segmentation Using a Classification Framework Co-segmentation Using Graph Convolutional Network Conditional Siamese Convolutional Network Few-shot Learning for Co-segmentation Conclusions

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Hati A. Image Co-segmentation 2023.pdf 9.8 MB

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hati image co segmentation 2023

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