Development of video-based emotion recognition using deep learning with Google colab
Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human fac...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English English |
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UAD
2020
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| Online Access: | http://irep.iium.edu.my/82532/ http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf |
| _version_ | 1848789313759739904 |
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| author | Gunawan, Teddy Surya Ashraf, Arselan Riza, Bob Subhan Haryanto, Edy Victor Rosnelly, Rika Kartiwi, Mira Janin, Zuriati |
| author_facet | Gunawan, Teddy Surya Ashraf, Arselan Riza, Bob Subhan Haryanto, Edy Victor Rosnelly, Rika Kartiwi, Mira Janin, Zuriati |
| author_sort | Gunawan, Teddy Surya |
| building | IIUM Repository |
| collection | Online Access |
| description | Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set. |
| first_indexed | 2025-11-14T17:54:44Z |
| format | Article |
| id | iium-82532 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:54:44Z |
| publishDate | 2020 |
| publisher | UAD |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-825322021-02-11T06:55:57Z http://irep.iium.edu.my/82532/ Development of video-based emotion recognition using deep learning with Google colab Gunawan, Teddy Surya Ashraf, Arselan Riza, Bob Subhan Haryanto, Edy Victor Rosnelly, Rika Kartiwi, Mira Janin, Zuriati TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set. UAD 2020-10 Article PeerReviewed application/pdf en http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf application/pdf en http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf Gunawan, Teddy Surya and Ashraf, Arselan and Riza, Bob Subhan and Haryanto, Edy Victor and Rosnelly, Rika and Kartiwi, Mira and Janin, Zuriati (2020) Development of video-based emotion recognition using deep learning with Google colab. Telkomnika, 18 (5). pp. 2463-2471. ISSN 1693-6930 http://journal.uad.ac.id/index.php/TELKOMNIKA 10.12928/telkomnika.v18i5.16717 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Gunawan, Teddy Surya Ashraf, Arselan Riza, Bob Subhan Haryanto, Edy Victor Rosnelly, Rika Kartiwi, Mira Janin, Zuriati Development of video-based emotion recognition using deep learning with Google colab |
| title | Development of video-based emotion recognition using deep learning with Google colab |
| title_full | Development of video-based emotion recognition using deep learning with Google colab |
| title_fullStr | Development of video-based emotion recognition using deep learning with Google colab |
| title_full_unstemmed | Development of video-based emotion recognition using deep learning with Google colab |
| title_short | Development of video-based emotion recognition using deep learning with Google colab |
| title_sort | development of video-based emotion recognition using deep learning with google colab |
| topic | TK Electrical engineering. Electronics Nuclear engineering TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices |
| url | http://irep.iium.edu.my/82532/ http://irep.iium.edu.my/82532/ http://irep.iium.edu.my/82532/ http://irep.iium.edu.my/82532/7/82532_Development%20of%20video-based%20emotion%20recognition.pdf http://irep.iium.edu.my/82532/8/82532_Development%20of%20video-based%20emotion%20recognition_Scopus.pdf |