Scaling Depression Level Through Facial Image Processing and Social Media Analysis
Author:
Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-1089-9_71
Reference18 articles.
1. Islam M, Kabir M, Ahmed A, Kamal A, Wang H, Ulhaq A (2018) Depression detection from social network data using machine learning techniques. Health Inf Sci Syst 6(1):8. https://doi.org/10.1007/s13755-018-0046-0
2. Viola P, Jones M, Rapid object detection using a boosted cascade of simple features. https://doi.org/10.1109/CVPR.2001.990517
3. Zhu Y, Shang Y, Shao Z, Guo G (2017) Automated depression diagnosis based on deep networks to encode facial appearance and dynamics.: IEEE Trans Affect Comput 9(4):578–584. https://doi.org/10.1109/TAFFC.2017.2650899
4. Alghowinem S, Goecke R, Cohn J, Wagner M, Parker G, Breakspear M, Cross-cultural detection of depression from nonverbal behaviour. https://doi.org/10.1109/FG.2015.7163113
5. Jraidi I, Chaouachi M, Frasson C, A dynamic multimodal approach for assessing learners’ interaction experience. https://doi.org/10.1145/2522848.2522896
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