Publication | Closed Access
A Summarization of the Visual Depression Databases for Depression Detection
22
Citations
22
References
2020
Year
Unknown Venue
EngineeringAppropriate DatasetMental HealthPsychologySocial SciencesText MiningImage AnalysisData ScienceMood SymptomPattern RecognitionAffective ComputingPsychiatryVisual DiagnosisDepressionVisual Data MiningPsychiatric DisorderMood SpectrumDepression Detection ModelMental Health MonitoringDepression Detection ModelsVisual Depression DatabasesPsychopathologyPost-traumatic Stress Disorder
Depression is a serious, pervasive mental issue in our general public. A large portion of the populace experiences this issue. Thus there is an outrageous requirement for the depression detection models, which will offer a helpful framework and early identification of depression. There is an essential need for relevant data to set up a depression detection model. This paper presents a brief summarization regarding ten depression datasets available, which will guide the researchers to select an appropriate dataset for their depression detection models. This summarization has been done over the non-verbal signs of depression, data collection techniques, clinical definition, and annotations. Moreover, a tabular list of datasets is provided for quick and easy look through.
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