Graph Attention Model Embedded With Multi-Modal Knowledge For Depression Detection

Published: Jul 1, 2020
Abstract
With more than 300 million people depressed worldwide annually, depression is a global problem. The goal of depression detection is to improve diagnostic accuracy and availability, leading to faster intervention. The most important and challenging problem here is to design an effective and robust depression detection model. To this end, there are two challenges to overcome: 1) Multi-modal (audio, image, text, etc.) information must be jointly...
Paper Details
Title
Graph Attention Model Embedded With Multi-Modal Knowledge For Depression Detection
Published Date
Jul 1, 2020
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