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Automated data processing and feature engineering for deep learning and big data applications: a survey
In addition to automating specific data processing tasks, we discuss the use of AutoML methods and tools to simultaneously optimize all stages of the machine learning pipeline.
A survey of synthetic data augmentation methods in computer vision
Since this is the first paper to explore synthetic data augmentation methods in great detail, we are hoping to equip readers with the necessary background information and in-depth knowledge of existing methods and their attendant issues.
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods
Finally, we carried out an extensive comparison and analysis of the performance of automated data augmentation techniques and state-of-the-art methods based on classical augmentation approaches.
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