CNN model for Depression Detection using JAFFE Dataset
DOI:
https://doi.org/10.5281/zenodo.4247798Keywords:
Convolutional Neural Networks, Depression, Local Binary Pattern, Accuracy, JAFFE datasetAbstract
Depression is one of the serious mental illnesses and a difficult illness to detect, due to it showing different symptoms in different individuals. It also becomes difficult to treat patients due to them not seeking help because of mental well-being given a backseat in the overall health of an individual, and the stigma present in the society about seeking help from psychologists. It is also seen that people try to downplay the symptoms when talking to a psychologist. Here, we have designed a CNN model which detects whether a person is depressed or not based on the facial features of the person.
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