“Depression.” [Online]. Available: https://www.who.int/health-topics/depression#tab=tab_1. [Accessed: 01-Feb-2020].
 T. P. Blackburn, “Depressive disorders: Treatment failures and poor prognosis over the last 50 years,” Pharmacol. Res. Perspect., vol. 7, no. 3, pp. 1–20, 2019.
 S. Al-Gawwam and M. Benaissa, “Depression Detection from Eye Blink Features,” in 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT, 2018, pp. 388–392.
 J. F. Cohn et al., “Detecting depression from facial actions and vocal prosody,” in Proceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009, 2009, pp. 1–7.
 P. VIOLA and M. J. JONES, “Robust Real-Time Face Detection,” Int. J. Eng. Technol., vol. 7, no. 2, pp. 29–32, 2004.
 T. Baltrušaitis, P. Robinson, and L.-P. Morency, “Constrained Local Neural Fields for robust facial landmark detection in the wild,” in In Proceedings of the IEEE international conference on computer vision workshops, 2013, pp. 354–361.
 E. S. Mikhailova, T. V. Vladimirova, A. F. Iznak, E. J. Tsusulkovskaya, and N. V. Sushko, “Abnormal recognition of facial expression of emotions in depressed patients with major depression disorder and schizotypal personality disorder,” Biol. Psychiatry, vol. 40, no. 8, pp. 697–705, Oct. 1996.
 Q. Wang, H. Yang, and Y. Yu, “Facial expression video analysis for depression detection in Chinese patients,” J. Vis. Commun. Image Represent. vol. 57, no. November, pp. 228–233, 2018.
 T. Baltrušaitis, M. Mahmoud, and P. Robinson, “Cross-dataset learning and person-specific normalization for automatic Action Unit detection,” in 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG, 2015, vol. 2015-Janua, pp. 1–6.
 İ. Babaoğlu, “Diagnosis of Coronary Artery Disease Using Artificial Bee Colony and K-Nearest Neighbor Algorithms,” Int. J. Comput. Commun. Eng., vol. 2, no. 1, pp. 56–59, 2013.
 I. Nurwauziyah, U. D. S, I. G. B. Putra, and M. I. Firdaus, “Satellite Image Classification using Decision Tree , SVM and k-Nearest Neighbor,” no. July, 2018.
 B. Schölkopf, “SVMs - A practical consequence of learning theory,” IEEE Intell. Syst. Their Appl., vol. 13, no. 4, pp. 18–21, Jul. 1998.
 A. Hulaj, A. Shehu, and X. Bajrami, “Support Vector Machine for the Classification of Images Captured by WMSN,” in Proceedings - 2017 International Conference on Control, Artificial Intelligence, Robotics and Optimization, ICCAIRO, 2017, pp. 283–287.
 Q. Wang, Q. Gao, X. Gao, and F. Nie, “Angle principal component analysis,” IJCAI Int. Jt. Conf. Artif. Intell., vol. 7, no. 5, pp. 2936–2942, 2017.
 B. J. Frey, “Pattern Classification,” in Graphical Models for Machine Learning and Digital Communication, 2018, p. 654.
 D. Acquisition et al., “Naval Postgraduate,” vol. 298, no. June, pp. 405–405, 2010.
 K. Torkkola, “Linear Discriminant Analysis in Document Classification,” in International Conference Data Mining Workshop on Text Mining, 2001, no. October, pp. 1–10.
 T. Qin, T. Y. Liu, X. D. Zhang, D. S. Wang, and H. Li, “Global ranking using Continuous Conditional Random Fields,” in Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference, 2009, pp. 1281–1288.
 G. Jackson-Koku, “Beck depression inventory,” Occup. Med. (Chic. Ill)., vol. 66, no. 2, pp. 174–175, 2016.
 N. C. Maddage, R. Senaratne, L. S. A. Low, M. Lech, and N. Allen, “Video-based detection of the clinical depression in adolescents,” in in Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC, 2015, pp. 3723–3726.
 G. Stratou, S. Scherer, J. Gratch, and L. Morency, “Automatic nonverbal behavior indicators of depression and PTSD : the effect of gender,” J. Multimodal User Interfaces, vol. 9, 2014.
 M. Senoussaoui, M. Sarria-paja, J. F. Santos, and T. H. Falk, “Model Fusion for Multimodal Depression Classification and Level Detection,” Proc. 4th Int. Work. Audio/Visual Emot. Challenge, 2014, pp. 57-63.
 S. Alghowinem, R. Goecke, J. F. Cohn, M. Wagner, G. Parker, and M. Breakspear, “Cross-cultural detection of depression from nonverbal behavior,” in 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG ,2015, pp. 1-8.
 T. H. Yang, C. H. Wu, K. Y. Huang, and M. H. Su, “Coupled HMM-based multimodal fusion for mood disorder detection through elicited audio–visual signals,” J. Ambient Intell. Humaniz. Comput., vol. 8, no. 6, pp. 895–906, 2017.
 S. Harati, A. Crowell, H. Mayberg, J. Kong, and S. Nemati, “Discriminating clinical phases of recovery from major depressive disorder using the dynamics of facial expression,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS,2016, pp. 2254–2257.
 J. M. Girard, J. F. Cohn, M. H. Mahoor, S. Mavadati, and D. P. Rosenwald, “Social risk and depression: Evidence from manual and automatic facial expression analysis,” 2013 10th IEEE Int. Conf. Work. Autom. Face Gesture Recognition, FG, pp. 1–8, and 2013.
 H. Dibeklioglu, Z. Hammal, and J. F. Cohn, “Dynamic Multimodal Measurement of Depression Severity Using Deep Autoencoding,” IEEE J. Biomed. Heal. Informatics, vol. 22, no. 2, pp. 525–536, 2018.
 A. Jan, H. Meng, Y. F. A. Gaus, F. Zhang, and S. Turabzadeh, “Automatic Depression Scale Prediction using Facial Expression Dynamics and Regression Categories and Subject Descriptors,” Proc. 4th Int. Work. Audio/Visual Emot. Chall., pp. 73–80, 2014.
 D. Venkataraman, “Extraction of Facial Features for Depression Detection among Students,” Int. J. Pure Appl. Math., vol. 118, no. 7, pp. 455–463, 2018.
 B. G. Dadiz, C. R. Ruiz, T. Manila, and Q. Manila, “Detecting Depression in Videos using Uniformed Local Binary Pattern on Facial Features,” pp. 413–422, 2019.
 J. M. Twenge, A. B. Cooper, T. E. Joiner, M. E. Duffy, and S. G. Binau, “Age, Period, and Cohort Trends in Mood Disorder Indicators and Suicide-Related Outcomes in a Nationally Representative Dataset, 2005-2017,” J. Abnorm. Psychol., vol. 128, no. 3, pp. 185–199, Apr. 2019.
 “Understand the News.” [Online]. Available: https://www.vox.com/. [Accessed: 09-Feb-2