SCRS Proceedings of International Conference of Undergraduate Students 2023
A Comprehensive Survey on Depression Detection Techniques
Authors: Yash Kandalkar, Sanket Kulkarni, Abdurrahman Yusufi, Raghav Dodla and Manjiri Ranjanikar
Publishing Date: 11-10-2023
ISBN: 978-81-955020-4-2
Abstract
Depression and mental diseases are significant problems in today's culture. It may result in suicidal thoughts.In this study, we analyze several earlier studies that identified depression using deep learning (DL), machine learning (ML), and artificial intelligence (AI).This study explores how emotions may be precisely identified, and how depressive symptoms can be communicated via social media posts, images, audio, and facial expressions. Linear Support Vector, Logistic Regression, Long Term Short Memory (LSTM), Naive-Bayes, Support Vector Machines (SVM), etc. are some of the ML approaches used to recognize and classify emotions from the data. Artificial neural networks (ANN) are used to classify and extract features from photographs to identify emotions from facial expressions. The purpose of this work is to present an overview of several AI, DL, and ML approaches that aid in the identification and study of emotion, and thereby depression, as well as the research concerns, they raise.
Keywords
Deep Learning, Image Processing, Machine Learning, Depression Detection, Audio Processing, Text Processing
Cite as
Yash Kandalkar, Sanket Kulkarni, Abdurrahman Yusufi, Raghav Dodla and Manjiri Ranjanikar, "A Comprehensive Survey on Depression Detection Techniques", In: Deepak Bhatia and Himanshu Arora (eds), SCRS Proceedings of International Conference of Undergraduate Students 2023, SCRS, India, 2023, pp. 25-34. https://doi.org/10.56155/978-81-955020-4-2-3