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Image Co-segmentation

Bag om Image Co-segmentation

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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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789811985720
  • Indbinding:
  • Paperback
  • Sideantal:
  • 236
  • Udgivet:
  • 3. februar 2024
  • Udgave:
  • 24001
  • Størrelse:
  • 155x13x235 mm.
  • Vægt:
  • 365 g.
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 18. december 2024
Forlænget returret til d. 31. januar 2025

Beskrivelse af Image Co-segmentation

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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