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Development of video-based emotion recognition using deep learning with Google colab

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

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Abstract

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.

Item Type: Article (Journal)
Additional Information: 5588/82532
Uncontrolled Keywords: Convolutional neural networks Deep learning Emotion recognition Google Colab Machine learning
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Teddy Surya Gunawan
Date Deposited: 01 Sep 2020 15:25
Last Modified: 01 Sep 2020 15:25
URI: http://irep.iium.edu.my/id/eprint/82532

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