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Software Engineering for Dataset Augmentation using Generative Adversarial Networks
Jahic, Benjamin; Guelfi, Nicolas; Ries, Benoît
2019In Proceedings of 10th IEEE International Conference on Software Engineering and Service Science
Peer reviewed
 

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Keywords :
software engineering; development process; dataset engineering; automated data generation; neural network training
Abstract :
[en] 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 handwritten digits using conditional generative adversarial networks (cGAN). Finally, we shortly discuss selected important issues of our process, presenting related work and proposing some improvements.
Disciplines :
Computer science
Author, co-author :
Jahic, Benjamin ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Guelfi, Nicolas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Ries, Benoît ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
no
Language :
English
Title :
Software Engineering for Dataset Augmentation using Generative Adversarial Networks
Publication date :
19 October 2019
Event name :
10th IEEE International Conference on Software Engineering and Service Science
Event place :
Beijing, China
Event date :
from 18-10-2019 to 20-10-2019
Audience :
International
Main work title :
Proceedings of 10th IEEE International Conference on Software Engineering and Service Science
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 01 July 2019

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