Deep Learning based model for Depression Detection

Abstract

Major Depressive Disorder(MDD) or Depression is the most prevalent psychiatric disorder in the world. This paper aims to apply deep learning techniques to detect the prevalence of depression using the clinically approved dataset. The paper aims at developing a system for early detection of depression in students .The proposed model comprises CNN (Convolutional Neural Network), which is the most widely used for the tasks involving the computer vision and GAN (Generative Adversarial Network), which can be used as a transfer learning approach for the same. The early diagnosis can create a scope for intervention and thus , alleviate the worst effects of clinical depression.