| 书目名称 | Image Co-segmentation | | 编辑 | Avik Hati,Rajbabu Velmurugan,Subhasis Chaudhuri | | 视频video | | | 概述 | Introduces novel computer science concepts of maximally occurring common subgraph matching.Provides complete algorithmic details for the ease of implementation and reproducibility by practitioners in | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | .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.. | | 出版日期 | Book 2023 | | 关键词 | subgraph matching; label propagation; graph convolutional neural network; conditional encoder-decoder; m | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-19-8570-6 | | isbn_softcover | 978-981-19-8572-0 | | isbn_ebook | 978-981-19-8570-6Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 16:59:37
