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Research Article

Emotion Recognition Using Convolution Neural Networks: Analysis on FER 2013 Dataset

  • Paper ID 114
  • Volume 4, Issue 2
  • Pages 27-30
  • Published Online: March-April 2024
  • 6 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Gurshish Sarabjit Bedi1
  • Dr. Jayasree Ravi2

1,2 Department of Computer Science, SVKM's Mithibai College of Arts, Chauhan Institute of Science & Amrutben Jivanlal College of Commerce And Economics (AUTONOMOUS), Maharashtra, India.

Article Information

Published Online
March-April 2024
Pages
27-30
Article Type
Research Article
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References

1. Liliana, D.Y.: Emotion recognition from facial expression using deep convolutional neural network. Journal of Physics, Conference Series
1193 (2018)
2. Ding, H., Zhou, S.K., Chellappa, R.: FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition 7 (2016)
3. Li, S., Deng, W.: Deep facial expression recognition: A survey. IEEE Transactions on Affective Computing 13(3), 1195–1215 (2022).
https://doi.org/10.1109/ TAFFC.2020.2981446
4. Kumari, J., Rajesh, R., Pooja, K.M.: Facial expression recognition: A survey. Procedia Computer Science 58, 486–491 (2015). https:
//doi.org/10.1016/j.procs.2015.08.011. Second International Symposium on Computer Vision and the Internet (VisionNet’15)
5. Rawat, W., Wang, Z.: Deep convolutional neural networks for image classification: A comprehensive review. Neural Computation 29, 1–98
(2017). https://doi.org/10.1162/ NECO_a_00990
6. Al-Nafjan, A., Hosny, M., Al-Wabil, A., AlOhali, Y.: Classification of human emotions from electroencephalogram (eeg) signal using deep
neural network. International Journal of Advanced Computer Science and Applications 8(9) (2017). https://doi.org/10.14569/
IJACSA.2017.080955
7. Alakus, T.B., Gonen, M., Turkoglu, I.: Database for an emotion recognition system based on eeg signals and various computer games –
gameemo. Biomedical Signal Processing and Control 60, 101951 (2020). https: //doi.org/10.1016/j.bspc.2020.101951
8. Alhagry, S., Fahmy, A.A., El-Khoribi, R.A.: Emotion recognition based on eeg using lstm recurrent neural network. International Journal of
Advanced Computer Science and Applications 8(10) (2017). https://doi.org/ 10.14569/IJACSA.2017.081046
9. Muhamed Ali, A., Ibrahim, A., Zhuang, H.: An approach for facial expression classification. International Journal of Biometrics 9, 96 (2017).
https://doi.org/10.1504/IJBM. 2017.10006477
10. Sang, D.V., Van Dat, N., Thuan, D.P.: Facial expression recognition using deep convolutional neural networks. In: 2017 9th International
Conference on Knowledge and Systems Engineering (KSE), pp. 130–135 (2017). https://doi.org/10.1109/KSE.2017.8119447
11. [Mollahosseini, A., Chan, D., Mahoor, M.H.: Going deeper in facial expression recognition using deep neural networks. In: 2016 IEEE
Winter Conference on Applications of Computer Vision (WACV), pp. 1–10 (2016). https: //doi.org/10.1109/WACV.2016.7477450
12. Singh, S., Nasoz, F.: Facial expression recognition with convolutional neural networks. In: 2020 10th Annual Computing and Communication
Workshop and Conference (CCWC), pp. 0324–0328 (2020). https://doi.org/10. 1109/CCWC47524.2020.9031283
13. Gervasi, O., Franzoni, V., Riganelli, M., Tasso, S.: Automating facial emotion recognition. Web Intell. 17(1), 17–27 (2019)
14. Lydia, A., Francis, S.: Adagrad - an optimizer for stochastic gradient descent Volume 6, 566–568 (2019)
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