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Hati / Chaudhuri / Velmurugan

Image Co-segmentation

Medium: Buch
ISBN: 978-981-19-8572-0
Verlag: Springer Nature Singapore
Erscheinungstermin: 03.02.2024
Lieferfrist: bis zu 10 Tage

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.


Produkteigenschaften


  • Artikelnummer: 9789811985720
  • Medium: Buch
  • ISBN: 978-981-19-8572-0
  • Verlag: Springer Nature Singapore
  • Erscheinungstermin: 03.02.2024
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2023
  • Serie: Studies in Computational Intelligence
  • Produktform: Kartoniert
  • Gewicht: 365 g
  • Seiten: 221
  • Format (B x H x T): 155 x 235 x 13 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

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.