Child Emotion Recognition via Custom Lightweight CNN Architecture

Muhammad Hussain; Hussain Al-Aqrabi

doi:10.1007/978-3-031-21199-7_12

Child Emotion Recognition via Custom Lightweight CNN Architecture

Muhammad Hussain, Hussain Al-Aqrabi

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Citations (Scopus)

Abstract

Advancements in e-learning coupled with the recent pandemic has resulted in a paradigm shift when it comes to remote-based education. Whilst this has its benefits the most important being the continuation of the curriculum there are various risks posed to younger learners. Their exposure to a wide variety of content including that with malicious intent poses a serious risk to the emotional well being of children and is a concern for parents. This chapter presents online child emotion recognition framework enabling parents to monitor their childs well-being whilst engaging with online content. The framework is a result of breakthroughs in deep learning for facilitating the development of lightweight convolutional neural networks that can be deployed without the need for specific hardware requiring Graphical Processing Units. The chapter also covers the security concerns presenting an offline rather than a cloud-based inference mechanism.

Original language	English
Title of host publication	Kids Cybersecurity Using Computational Intelligence Techniques
Editors	Wael M. S. Yafooz, Hussain Al-Aqrabi, Arafat Al-Dhaqm, Abdelhamid Emara
Publisher	Springer, Cham
Pages	165-174
Number of pages	10
Volume	1080 SCI
Edition	1st
ISBN (Electronic)	9783031211997
ISBN (Print)	9783031211980, 9783031212017
DOIs	https://doi.org/10.1007/978-3-031-21199-7_12
Publication status	Published - 21 Feb 2023

Publication series

Name	Studies in Computational Intelligence
Publisher	Springer Cham
Volume	1080 SCI
ISSN (Print)	1860-949X
ISSN (Electronic)	1860-9503

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-031-21199-7_12Licence: Unspecified

Cite this

Hussain, M., & Al-Aqrabi, H. (2023). Child Emotion Recognition via Custom Lightweight CNN Architecture. In W. M. S. Yafooz, H. Al-Aqrabi, A. Al-Dhaqm, & A. Emara (Eds.), Kids Cybersecurity Using Computational Intelligence Techniques (1st ed., Vol. 1080 SCI, pp. 165-174). (Studies in Computational Intelligence; Vol. 1080 SCI). Springer, Cham. https://doi.org/10.1007/978-3-031-21199-7_12

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Hussain, M & Al-Aqrabi, H 2023, Child Emotion Recognition via Custom Lightweight CNN Architecture. in WMS Yafooz, H Al-Aqrabi, A Al-Dhaqm & A Emara (eds), Kids Cybersecurity Using Computational Intelligence Techniques. 1st edn, vol. 1080 SCI, Studies in Computational Intelligence, vol. 1080 SCI, Springer, Cham, pp. 165-174. https://doi.org/10.1007/978-3-031-21199-7_12

Child Emotion Recognition via Custom Lightweight CNN Architecture. / Hussain, Muhammad; Al-Aqrabi, Hussain.

Kids Cybersecurity Using Computational Intelligence Techniques. ed. / Wael M. S. Yafooz; Hussain Al-Aqrabi; Arafat Al-Dhaqm; Abdelhamid Emara. Vol. 1080 SCI 1st. ed. Springer, Cham, 2023. p. 165-174 (Studies in Computational Intelligence; Vol. 1080 SCI).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AU - Al-Aqrabi, Hussain

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KW - Convolutional neural networks

KW - Cyber security

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KW - Offline inference

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Child Emotion Recognition via Custom Lightweight CNN Architecture

Abstract

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Custom Lightweight Convolutional Neural Network Architecture For Automated Detection of Damaged Pallet Racking In Warehousing & Distribution Centers

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