Estimating Depression Severity from Long-Sequence Face Videos via an Ensemble Global Diverse Convolutional Model

Keyphrases

• Affective Computing 16%
• Clinical Interview 16%
• Cognitive Ability 16%
• Computer Vision Techniques 16%
• Computing Systems 16%
• Convolution Model 100%
• Deep Learning Model 16%
• Depression Analysis 16%
• Depression Diagnosis 16%
• Depression Severity 100%
• Diagnostic Aid 16%
• Ensemble Model 33%
• Face Video 100%
• Facial Movement 33%
• Long Sequence 100%
• Long-range Dependence 16%
• Machine Learning 16%
• Mood Disorders 16%
• Motivation 16%
• Movement Data 16%
• Multimodal Cues 16%
• Patient Comorbidities 16%
• Questionnaire Interview 16%
• Spatiotemporal Pattern 16%
• Speech Analysis 16%
• Unimodal Cue 16%
• Video Analysis 16%
• Video Data 16%

Computer Science

• Affective Computing 50%
• Clinical Interview 50%
• Computer Vision 50%
• Convolution 100%
• Deep Learning Model 50%
• Learning System 50%
• Machine Learning 50%
• Range Dependency 50%
• Speech Analysis 50%
• Temporal Information 50%