Reinhard Heckel

Deep Learning for Computational Imaging

• Broschiertes Buch

Produktbeschreibung

This textbook offers an introduction to deep learning for solving inverse problems. It introduces deep neural networks and deep neural network based signal and image reconstruction techniques. It discusses robustness aspects, how to evaluate and test different methods, and data-centric aspects.

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Produktdetails

• Verlag: Oxford University Press
• Seitenzahl: 224
• Erscheinungstermin: 30. April 2025
• Englisch
• Abmessung: 234mm x 156mm
• ISBN-13: 9780198947189
• ISBN-10: 0198947186
• Artikelnr.: 72177288

Inhaltsangabe

1: Introduction
2: Solving inverse problems with optimization tasks
3: Solving optimization problems
4: Sparse modelling
5: Plug-and-play methods
6: Learning to solve inverse problems end-to-end
7: Unrolled neural networks
8: Self-supervised learning
9: Signal reconstruction via imposing generative priors
10: Diffusion models
11: Signal reconstruction with un-trained neural networks
12: Coordinate-based multi-layer perceptrons
13: Robustness to perturbations
14: Datasets and evaluation of image reconstruction methods
15: Advanced reconstruction problems
16: Mathematical background