IIUM Repository

Affective computing for visual emotion recognition using convolutional neural networks

Ashraf, Arselan and Gunawan, Teddy Surya and Sophian, Ali and Ambikairajah, Eliathamby and Ihsanto, Eko and Kartiwi, Mira (2020) Affective computing for visual emotion recognition using convolutional neural networks. In: Springer’s Advances in Intelligent Systems and Computing (AISC). Springer, pp. 1-11. (In Press)

[img] PDF - Supplemental Material
Restricted to Registered users only

Download (2MB) | Request a copy
[img] PDF - Accepted Version
Restricted to Registered users only

Download (863kB) | Request a copy

Abstract

Affective computing is a developing interdisciplinary examination field uniting specialists and experts from different fields, going from artificial intelligence, nat-ural language processing, to intellectual and sociologies. The thought behind Af-fective Computing is to give PCs the aptitude of insight that will, in general, comprehend human feelings. Notwithstanding, these victories, the field needs hypothetical firm establishments and efficient rules in numerous regions, espe-cially so in feeling demonstrating and the development of computational models of feeling. This exploration manages Affective Computing to improve the exhibi-tion of Human-Machine Interaction. The focal point of this work is to distinguish the emotional state of a human utilizing deep learning procedure, i.e. Convolu-tional Neural Networks (CNN). The Warsaw Set of Emotional Facial Expression Pictures dataset has been utilized to build up a feeling acknowledgement model which will have the option to perceive five facial feelings, including happy, sad, anger, surprise and neutral. The proposed framework design and the strategy has been discussed in this paper alongside the experimental findings.

Item Type: Book Chapter
Additional Information: 5588/86114
Uncontrolled Keywords: Affective Computing, Artificial Intelligence, Emotion Recognition, Convolutional Neural Networks
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 17 Dec 2020 15:16
Last Modified: 17 Dec 2020 15:16
URI: http://irep.iium.edu.my/id/eprint/86114

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year