Taking All the Factors We Need: A Multimodal Depression Classification With Uncertainty Approximation
Author:
Affiliation:
1. Institute of Information Technology, Jahangirnagar University, Dhaka, Bangladesh
2. Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Funder
Institutional Fund Projects funded by the Ministry of Education
King Abdulaziz University Deanship of Scientific Research (DSR), Jeddah, Saudi Arabia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10250425.pdf?arnumber=10250425
Reference58 articles.
1. Exploring the dominant features of social media for depression detection
2. SparNet: A Convolutional Neural Network for EEG Space-Frequency Feature Learning and Depression Discrimination
3. Early Depression Detection from Social Network Using Deep Learning Techniques
4. Speech emotion recognition using deep 1D & 2D CNN LSTM networks
5. Survey of Depression Detection using Social Networking Sites via Data Mining
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