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Related Questions
- What are some common applications of data augmentation in neural networks?
- How can generative models like GANs be used to synthesize missing data in a dataset?
- What techniques can be used to optimize the performance of generative models in data augmentation tasks?
- What are some potential pitfalls when using generative models to augment training data?
- Can you walk me through an example of how data augmentation can help improve the performance of a machine learning model?
- How can noise injection and other forms of data augmentation be used in conjunction with generative models?
- Are there any specific scenarios or domains where data augmentation techniques are particularly effective in terms of increasing diversity and representativeness of training data?
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