A CNN Based Approach for Depression Detection

Since the emergence of large information, recognising facial expressions (FER) has become an important topic in deep learning. Human psychological functioning is symbolised by the human symbol. Expressions on the face can disclose a great deal about human beings. At this point, melancholy had reached the status of a serious psychological illness. Recognising melancholy individuals is essential. We proposed a technique using CNN, Open CV, and a Haar Cascades Classification for detecting melancholy. The Haas Cascade Classifier is a form of AI where the machines learn by themselves detects faces. The proposed combination method employs layers of convolution. In addition, there are no accessible data sets that record genuine emotions of the melancholy visage and can be utilised for diagnosing melancholy. Consequently, we compiled a 5000-person Depressive and Not Depressive (DND) dataset. The proposed combination method employs convolution layers. In addition, there are no publicly accessible data sets that record the natural emotions of the melancholy visage and can be utilised for diagnosing depression.