Image co-segmentation / / Avik Hati [and three others]

• Autore: Hati Avik
• Pubblicazione: Singapore : , : Springer, , [2023]; ©2023
• Edizione: 1st ed. 2023.
• Descrizione fisica: 1 online resource (231 pages)
• Disciplina: 006.6
• Soggetto topico: Image segmentation
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Image co-segmentation
• ISBN: 981-19-8570-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910647769903321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in computational intelligence ; ; Volume 1082.