Training the Fer2013 Dataset with Keras Tuner

Benyoussef Abdellaoui; Aniss Moumen; Younes El Bouzekri El Idrissi; Ahmed Remaida

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Paper

Training the Fer2013 Dataset with Keras Tuner

In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning BML - Volume 1, 409-412, 2021 , Kenitra, Morocco

Authors: Benyoussef Abdellaoui ; Aniss Moumen ; Younes El Bouzekri El Idrissi and Ahmed Remaida

Affiliation: Laboratory of Engineering Sciences, National School of Applied Sciences, Ibn Tofaïl University, Kenitra, Morocco

Keyword(s): Keras tuner, fer2013, CNN

Abstract: The emotional state of humans plays an essential role in the communication between humans and human-machine. The construction of a model capable of detecting emotions during a scene requires the adjustment of the model parameters. However, this adjustment is not easy. In this article, we use the Keras tuner module to find the hyperparameters during training fer2013 dataset with the CNN algorithm. The use of the Keras tuner reduces the time and optimizes the model with the best parameters.

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Paper citation in several formats:

Abdellaoui, B.; Moumen, A.; El Bouzekri El Idrissi, Y. and Remaida, A. (2022). Training the Fer2013 Dataset with Keras Tuner. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML; ISBN 978-989-758-559-3, SciTePress, pages 409-412. DOI: 10.5220/0010735600003101

@conference{bml22,
author={Benyoussef Abdellaoui. and Aniss Moumen. and Younes {El Bouzekri El Idrissi}. and Ahmed Remaida.},
title={Training the Fer2013 Dataset with Keras Tuner},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML},
year={2022},
pages={409-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010735600003101},
isbn={978-989-758-559-3},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - BML
TI - Training the Fer2013 Dataset with Keras Tuner
SN - 978-989-758-559-3
AU - Abdellaoui, B.
AU - Moumen, A.
AU - El Bouzekri El Idrissi, Y.
AU - Remaida, A.
PY - 2022
SP - 409
EP - 412
DO - 10.5220/0010735600003101
PB - SciTePress