Deep Learning for Computational Imaging
$140.84
- Paperback
240 pages
- Release Date
22 July 2025
Summary
Deep Learning for Image Reconstruction: A Comprehensive Guide
Computational imaging techniques are revolutionizing fields like microscopy, astronomy, and medical imaging by enabling high-resolution reconstructions from limited or noisy data. Traditionally, these inverse problems were tackled with expert-designed methods. However, deep learning has emerged as a powerful alternative, achieving state-of-the-art results.
This book offers the first comprehensive introduction to d…
Book Details
| ISBN-13: | 9780198947189 |
|---|---|
| ISBN-10: | 0198947186 |
| Author: | Prof Reinhard Heckel, Reinhard Heckel |
| Publisher: | Oxford University Press |
| Imprint: | Oxford University Press |
| Format: | Paperback |
| Number of Pages: | 240 |
| Release Date: | 22 July 2025 |
| Weight: | 406g |
| Dimensions: | 234mm x 157mm x 15mm |
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About The Author
Prof Reinhard Heckel
Reinhard Heckel is a Professor of Machine Learning at the Department of Computer Engineering at the Technical University of Munich (TUM), and adjunct faculty at Rice University. He was an assistant professor of Electrical and Computer Engineering from 2017-2019. Before that, he was a postdoctoral researcher in the Berkeley Artificial Intelligence Research Lab at UC Berkeley, and before that a researcher at IBM Research Zurich. He completed his PhD in 2014 at ETH Zurich and was a visiting PhD student at Stanford University’s Statistics Department. Reinhard’s work is centered on machine learning, artificial intelligence, and information processing, with a focus on developing algorithms and foundations for deep learning, particularly for medical imaging, on establishing mathematical and empirical underpinnings for machine learning, and on the utilization of DNA as a digital information technology.
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