S. Porcu, A. Floris, L. Atzori

Most of Facial Expression Recognition (FER) systems rely on machine learning approaches that require large databases (DBs) for an effective training. As these are not easily available, a good solution is to augment the DBs with appropriate techniques, which are typically based on either geometric transformation or deep learning based technologies (e.g., Generative Adversarial Networks (GANs)). Whereas the first category of techniques have been fairly adopted in the past, studies that use GAN-based techniques are limited for FER systems.

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[1] Simone Porcu, Alessandro Floris, Luigi Atzori, "GAN Generated Images for Facial Expression Recognition systems", IEEE Dataport, 2021. [Online]. Available: http://dx.doi.org/10.21227/b7m1-rz14. Accessed: Oct. 20, 2021.
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doi = {10.21227/b7m1-rz14},
url = {http://dx.doi.org/10.21227/b7m1-rz14},
author = {Simone Porcu; Alessandro Floris; Luigi Atzori },
publisher = {IEEE Dataport},
title = {GAN Generated Images for Facial Expression Recognition systems},
year = {2021} }
TY - DATA
T1 - GAN Generated Images for Facial Expression Recognition systems
AU - Simone Porcu; Alessandro Floris; Luigi Atzori
PY - 2021
PB - IEEE Dataport
UR - 10.21227/b7m1-rz14
ER -
Simone Porcu, Alessandro Floris, Luigi Atzori. (2021). GAN Generated Images for Facial Expression Recognition systems. IEEE Dataport. http://dx.doi.org/10.21227/b7m1-rz14
Simone Porcu, Alessandro Floris, Luigi Atzori, 2021. GAN Generated Images for Facial Expression Recognition systems. Available at: http://dx.doi.org/10.21227/b7m1-rz14.
Simone Porcu, Alessandro Floris, Luigi Atzori. (2021). "GAN Generated Images for Facial Expression Recognition systems." Web.
1. Simone Porcu, Alessandro Floris, Luigi Atzori. GAN Generated Images for Facial Expression Recognition systems [Internet]. IEEE Dataport; 2021. Available from : http://dx.doi.org/10.21227/b7m1-rz14
Simone Porcu, Alessandro Floris, Luigi Atzori. "GAN Generated Images for Facial Expression Recognition systems." doi: 10.21227/b7m1-rz14