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Affective computing for visual emotion recognition using convolutional neural networks

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 ins...

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Main Authors: Ashraf, Arselan, Gunawan, Teddy Surya, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko, Kartiwi, Mira
Format: Book Chapter
Language:English
English
English
Published: Springer 2021
Subjects:
TK7885 Computer engineering
Online Access:http://irep.iium.edu.my/86114/1/86114_Acceptance%20letter.pdf
http://irep.iium.edu.my/86114/8/86114_Affective%20computing%20for%20visual%20emotion%20recognition.pdf
http://irep.iium.edu.my/86114/14/86114_Affective%20computing%20for%20visual%20emotion%20recognition-scopus.pdf
http://irep.iium.edu.my/86114/
https://icites2020.ump.edu.my/index.php/en/
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spelling my.iium.irep.861142021-05-11T02:04:51Z http://irep.iium.edu.my/86114/ Affective computing for visual emotion recognition using convolutional neural networks Ashraf, Arselan Gunawan, Teddy Surya Sophian, Ali Ambikairajah, Eliathamby Ihsanto, Eko Kartiwi, Mira TK7885 Computer engineering 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. Springer 2021 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/86114/1/86114_Acceptance%20letter.pdf application/pdf en http://irep.iium.edu.my/86114/8/86114_Affective%20computing%20for%20visual%20emotion%20recognition.pdf application/pdf en http://irep.iium.edu.my/86114/14/86114_Affective%20computing%20for%20visual%20emotion%20recognition-scopus.pdf Ashraf, Arselan and Gunawan, Teddy Surya and Sophian, Ali and Ambikairajah, Eliathamby and Ihsanto, Eko and Kartiwi, Mira (2021) Affective computing for visual emotion recognition using convolutional neural networks. In: Springer’s Advances in Intelligent Systems and Computing (AISC). Springer, pp. 11-20. ISBN 9783030709167 https://icites2020.ump.edu.my/index.php/en/
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Ashraf, Arselan
Gunawan, Teddy Surya
Sophian, Ali
Ambikairajah, Eliathamby
Ihsanto, Eko
Kartiwi, Mira
Affective computing for visual emotion recognition using convolutional neural networks
description 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.
format Book Chapter
author Ashraf, Arselan
Gunawan, Teddy Surya
Sophian, Ali
Ambikairajah, Eliathamby
Ihsanto, Eko
Kartiwi, Mira
author_facet Ashraf, Arselan
Gunawan, Teddy Surya
Sophian, Ali
Ambikairajah, Eliathamby
Ihsanto, Eko
Kartiwi, Mira
author_sort Ashraf, Arselan
title Affective computing for visual emotion recognition using convolutional neural networks
title_short Affective computing for visual emotion recognition using convolutional neural networks
title_full Affective computing for visual emotion recognition using convolutional neural networks
title_fullStr Affective computing for visual emotion recognition using convolutional neural networks
title_full_unstemmed Affective computing for visual emotion recognition using convolutional neural networks
title_sort affective computing for visual emotion recognition using convolutional neural networks
publisher Springer
publishDate 2021
url http://irep.iium.edu.my/86114/1/86114_Acceptance%20letter.pdf
http://irep.iium.edu.my/86114/8/86114_Affective%20computing%20for%20visual%20emotion%20recognition.pdf
http://irep.iium.edu.my/86114/14/86114_Affective%20computing%20for%20visual%20emotion%20recognition-scopus.pdf
http://irep.iium.edu.my/86114/
https://icites2020.ump.edu.my/index.php/en/
_version_ 1701162769520263168
score 13.211869

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