Synthetic Data for Machine Learning

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Synthetic-to-Real Domain Adaptation

This chapter introduces you to a well-known issue that usually limits the usability of synthetic data, called the domain gap problem. In this chapter, you will learn various approaches to bridge this gap, which will help you to better leverage synthetic data. At the same time, the chapter discusses current state-of-the-art research on synthetic-to-real domain adaptation. Thus, you will learn which methods you may use for your own problems. Then, it represents the challenges and issues in this context to better comprehend the problem.

In this chapter, we’re going to cover the following main topics:

• The domain gap problem in ML
• Approaches for synthetic-to-real domain adaptation
• Synthetic-to-real domain adaptation ...