Software Engineering for Dataset Augmentation using Generative Adversarial Networks

@article{Jahic2019SoftwareEF,
  title={Software Engineering for Dataset Augmentation using Generative Adversarial Networks},
  author={Benjamin Jahic and Nicolas Guelfi and B. Ries},
  journal={2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS)},
  year={2019},
  pages={59-66}
}
  • Benjamin Jahic, Nicolas Guelfi, B. Ries
  • Published 2019
  • Computer Science
  • 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS)
  • Software engineers require a large amount of data for building neural network-based software systems. The engineering of these data is often neglected, though, it is a critical and time-consuming activity. In this work, we present a novel software engineering approach for dataset augmentation using neural networks. We propose a rigorous process for generating synthetic data to improve the training of neural networks. Also, we demonstrate our approach to successfully improve the recognition of… CONTINUE READING
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