Depression is the most common mood disorder, and people who have experienced depression often are at risk for mental and potentially physical disorders. As a response, machine-based depression analysis has gotten a lot of interest in recent years. Humans’ facial expressions and emotions appear different when they are in a depressed state than when they are in a positive mood. Depressed people may feel sad, anxious, hopeless, empty, worried, helpless, worthless, hurt, irritable, guilty, or restless. In the proposed system, we proposed a facial dataset and a CNN method to train the dataset and generate a CNN model. The harr cascade method is used to identify facial expression. The final output is used to determine whether or not a person is depressed.
₹10000 (INR)
NON IEEE -2022