On the review of image and video-based depression detection using machine learning

Ashraf, Arselan and Gunawan, Teddy Surya and Riza, Bob Subhan and Haryanto, Edy Victor and Janin, Zuriati (2020) On the review of image and video-based depression detection using machine learning. Indonesian Journal of Electrical Engineering and Computer Science, 19 (3). pp. 1677-1684. ISSN 2502-4752

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Abstract

Machine learning has been introduced in the sphere of the medical field to enhance the accuracy, precision, and analysis of diagnostics while reducing laborious jobs. With the mounting evidence, machine learning has the capability to detect mental distress like depression. Since depression is the most prevalent mental disorder in our society at present, and almost the majority of the population suffers from this issue. Hence there is an extreme need for the depression detection models, which will provide a support system and early detection of depression. This review is based on the image and video-based depression detection model using machine learning techniques. This paper analyses the data acquisition techniques along with their databases. The indicators of depression are also reviewed in this paper. The evaluation of different researches, along with their performance parameters, is summarized. The paper concludes with remarks about the techniques used and the future scope of using the image and video-based depression prediction.

Item Type:	Article (Journal)
Additional Information:	5588/84796
Uncontrolled Keywords:	Data acquisition, depression database, depression prediction, machine learning
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 > Department of Electrical and Computer Engineering
Depositing User:	Prof. Dr. Teddy Surya Gunawan
Date Deposited:	16 Nov 2020 14:26
Last Modified:	27 Jan 2021 09:29
URI:	http://irep.iium.edu.my/id/eprint/84796

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