Fusing Local-Global Facial Features by NFFT for Automatic Depression Estimation-Reference-Cited by-同舟云学术

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Fusing Local-Global Facial Features by NFFT for Automatic Depression Estimation

Published:2023-12-05 Issue: Volume:10 Page:1300-1305
ISSN:
Container-title:2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
language:
Short-container-title:

Author:

Ling Tianfei¹,Chen Deyuan¹,Zhu Tingshao²,Li Baobin³

Affiliation:

1. University of Chinese Academy of Sciences,School of Electronic, Electrical and Communication Engineering,China

2. Chinese Academy of Sciences,Institute of Psychology,Beijing,China

3. University of Chinese Academy of Sciences,School of Computer Science and Technology,Beijing,China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385250/10385251/10385416.pdf?arnumber=10385416

Reference29 articles.

1. Comparison of Beck Depression Inventories-IA and-II in Psychiatric Outpatients

2. Eye movement analysis for depression detection

3. AVEC 2014

4. Designing a framework for assisting depression severity assessment from facial image analysis

5. DepNet: An automated industrial intelligent system using deep learning for video‐based depression analysis

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