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

• 发表在: Indonesian Journal of Electrical Engineering and Computer Science
• 主要作者: 2-s2.0-85087900098
• 格式: 文件
• 语言: English
• 出版: Institute of Advanced Engineering and Science 2020
• 在线阅读: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087900098&doi=10.11591%2fijeecs.v19.i3.pp1677-1684&partnerID=40&md5=1cc504c299700c21c4a55ab88f169985

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. Copyright © 2020 Institute of Advanced Engineering and Science.