Page 102 - Read Online
P. 102
Page 87 Bah et al. Intell Robot 2022;2(1):7288 I http://dx.doi.org/10.20517/ir.2021.16
Ethical approval and consent to participate
In this study, we mainly used the FERGIT dataset which is a combination of the FER-2013 and muxspace
datasets. The FER2013 database was collected from the internet, and most pictures were captured in the wild
using search engine research.
Consent for publication
Not applicable.
Copyright
© The Author(s) 2022.
REFERENCES
1. Cowie R, Douglascowie E, Tsapatsoulis N, et al. Emotion recognition in humancomputer interaction. IEEE Signal Process Mag
2001;18:3280. DOI
2. Education, Alice Springs Mparntwe. 5E learning model, 284–5 7–38–55 Rule of Personal Communication, 36. feedback 2015;248:50.
3. Parkinson B, Manstead ASR. Current emotion research in social psychology: thinking about emotions and other People. Emotion Review
2015;7:37180. DOI
4. Waterloo SF, Baumgartner SE, Peter J, Valkenburg PM. Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram,
and WhatsApp. New Media Soc 2018;20:181331. DOI
5. LeBlanc VR, McConnell MM, Monteiro SD. Predictable chaos: a review of the effects of emotions on attention, memory and decision
making. Adv Health Sci Educ Theory Pract 2015;20:26582. DOI
6. Luz PM, Brown HE, Struchiner CJ. Disgust as an emotional driver of vaccine attitudes and uptake? A mediation analysis. Epidemiol Infect
2019;147:e182. DOI
7. Yonghao Z. Research on the humancomputer interaction design in mobile phones. 2020 International Conference on Computing and Data
Science (CDS) IEEE, 2020:395–399.
8. Chervyakov N, Lyakhov P, Kaplun D, Butusov D, Nagornov N. Analysis of the quantization noise in discrete wavelet transform filters for
image processing. Electronics 2018;7:135. DOI
9. Muslihah I, Muqorobin M. Texture characteristic of local binary pattern on face recognition with probabilistic linear discriminant analysis.
IJCIS 2020;1:226. DOI
10. Pitaloka DA, Wulandari A, Basaruddin T, Liliana DY. Enhancing CNN with preprocessing stage in automatic emotion recognition.
Procedia Computer Science 2017;116:5239. DOI
11. Nigam S, Singh R, Misra AK. Efficient facial expression recognition using histogram of oriented gradients in wavelet domain. Multimed
Tools Appl 2018;77:2872547. DOI
12. Deshpande NT, Ravishankar S. Face detection and recognition using violajones algorithm and fusion of PCA and ANN. Adv Comput
Sci Tech 2017;10;5:1173–89.
13. Chen Y, Jiang H, Li C, Jia X, Ghamisi P. Deep feature extraction and classification of hyperspectral images based on convolutional neural
networks. IEEE Trans Geosci Remote Sensing 2016;54:623251. DOI
14. He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. In:2016 Proceedings of the IEEE conference on computer
vision and pattern recognition. IEEE, 2016, pp. 770–8.
15. Liu ZS, Siu WC, Huang JJ. Image superresolution via weighted random forest. In:2017 IEEE International Conference on Industrial
Technology (ICIT). IEEE 2017, pp. 101923.
16. Hasani B, Mahoor MH. Spatiotemporal facial expression recognition using convolutional neural networks and conditional random fields.
In:2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017). IEEE, 2017, pp. 7905. DOI
17. Minaee S, Minaei M, Abdolrashidi A. Deepemotion: facial expression recognition using attentional convolutional network. Sensors
(Basel) 2021;21:3046. DOI
18. Pham L, Vu TH Tran TA. Facial expression recognition using residual masking network. In: 2020 25th International Conference on
Pattern Recognition (ICPR). IEEE, 2021, pp. 45139. DOI
19. Pu L, Zhu L. Differential residual learning for facial expression recognition. In: 2021 The 5th International Conference on Machine
Learning and Soft Computing. IEEE, 2021, pp.1038. DOI
20. Chowanda A. Separable convolutional neural networks for facial expressions recognition. J Big Data 2021;8;117. DOI
21. Lee JH, Kim DH, Jeong SN. Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep
learning neural network. Oral Dis 2020;26:1528. DOI
22. Lin M, Chen Q, Yan S. Network in network. arXiv preprint arXiv:1312.4400 2013.
23. Zahara L, Musa P, Wibowo EP, Karim I, Musa SB. The facial emotion recognition (FER2013) dataset for prediction system of micro
expressions face using the convolutional neural network (CNN) algorithm based raspberry Pi. In: 2020 Fifth International Conference on
Informatics and Computing (ICIC). IEEE, 2020, pp. 19. DOI
24. Albawi S, Mohammed TA, AlZawi S. Understanding of a convolutional neural network. In: 2017 International Conference on Engineer
ing and Technology (ICET). IEEE, 2017, pp. 16. DOI
25. Agarap AF. Deep learning using rectified linear units (relu). arXiv preprint arXiv:1312.4400, 2018.