Abstract
Now a day’s supported visual and audio cues for automatic depression assessment may be a fast emerging research subject. This comprehensive evaluation of existing methodologies focuses on machine learning (ML) algorithm and image processing (IP) algorithm, as documented in over sixty articles over the last ten years. There is a visual indicator of depression, several data collection procedures are used, and finally examined the previous year or existing datasets. In this article describes techniques and algorithms as well as methods for dimensionality reduction, visual feature extraction, regression approaches, and classification decision procedures, and also various fusion tactics. A significant meta-analysis of published data is given, based on performance indicators that are robust to chance, to identify general trends and important pressing concerns for further research using visual and verbal cues alone or in combination with signals for automated depression evaluation The suggested work also used deep learning and natural language processing to estimate depression levels based on current video data.
Highlights
IntroductionPeople who are sad are completely unaware of their mental illness
Results are formed as a implementation of machine learning (ML) and image processing (IP) based application and results is generated on any web browsers for social community users to prevent various health and mental stress issues of patients as well as user’s in his daily life and social interaction time
We ran our tests on datasets that were freely available online
Summary
People who are sad are completely unaware of their mental illness. They are unable to detect the source of even minor dissatisfaction in themselves, and as a result, such users/people develop suicidal impulses. People are aware that they are depressed in certain conditions, but they are unwilling to seek help from anyone, owing to the erroneous sense of ‘humiliation' connected with depression. Recognizing the indications of depression in the early stages of depression is more beneficial [1]. Depression is diagnosed as early as the primary grades, and a simple one-hour conversation with a counsellor can be extremely beneficial. Revised Manuscript received on August 31, 2021.
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More From: International Journal of Recent Technology and Engineering (IJRTE)
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