1 Introduction
1.1 Paper structure
2 Problem statement
3 Related works
4 Background
4.1 Traditional algorithms
4.2 Variational Autoencoder (VAE)
4.3 Generative Adversarial Networks (GANs)
5 Evaluation metrics
5.1 External performance evaluation
5.2 GAN-related metrics
5.3 Similarity measurements
6 Data Augmentation algorithms review
6.1 Basic DA Methods
6.2 Data Augmentation through VAE
6.3 Data Augmentation through GAN
6.4 DA based on Dynamic Time Warping (DTW)
7 Discussion
7.1 Advantages
7.2 Disadvantages
7.3 Open issues and challenges
8 Conclusion