Synthetic Data for Deep Learning

Sergey I. Nikolenko ()
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Sergey I. Nikolenko: Synthesis AI

in Springer Optimization and Its Applications from Springer, currently edited by Pardalos, Panos, Thai, My T. and Du, Ding-Zhu

Date: 2021
ISBN: 978-3-030-75178-4
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Citations: View citations in EconPapers (9)

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Chapters in this book:

Ch Chapter 1 Introduction: The Data Problem

Sergey I. Nikolenko

Ch Chapter 10 Synthetic-to-Real Domain Adaptation and Refinement

Sergey I. Nikolenko

Ch Chapter 11 Privacy Guarantees in Synthetic Data

Sergey I. Nikolenko

Ch Chapter 12 Promising Directions for Future Work

Sergey I. Nikolenko

Ch Chapter 2 Deep Learning and Optimization

Sergey I. Nikolenko

Ch Chapter 3 Deep Neural Networks for Computer Vision

Sergey I. Nikolenko

Ch Chapter 4 Generative Models in Deep Learning

Sergey I. Nikolenko

Ch Chapter 5 The Early Days of Synthetic Data

Sergey I. Nikolenko

Ch Chapter 6 Synthetic Data for Basic Computer Vision Problems

Sergey I. Nikolenko

Ch Chapter 7 Synthetic Simulated Environments

Sergey I. Nikolenko

Ch Chapter 8 Synthetic Data Outside Computer Vision

Sergey I. Nikolenko

Ch Chapter 9 Directions in Synthetic Data Development

Sergey I. Nikolenko

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DOI: 10.1007/978-3-030-75178-4

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