1 |
B. K. Kim, J. Roh, S. Y. Dong, and S. Y. Lee, "Hierarchical committee of deep convolutional neural networks for robust facial expression recognition," Journal on Multimodal User Interfaces, vol. 10, no. 2, pp. 173-189, 2016.
DOI
|
2 |
G. Pons and D. Masip, "Supervised committee of convolutional neural networks in automated facial expression analysis," IEEE Transactions on Affective Computing, vol. 9, no. 3, pp. 343-350, 2018. https://doi.org/10.1109/TAFFC.2017.2753235
DOI
|
3 |
L. Chen, M. Zhou, W. Su, M. Wu, J. She, and K. Hirota, "Softmax regression based deep sparse autoencoder network for facial emotion recognition in human-robot interaction," Information Sciences, vol. 428, pp. 49- 61, 2018.
DOI
|
4 |
S. Eleftheriadis, O. Rudovic, and M. Pantic, "Discriminative shared gaussian processes for multiview and view-invariant facial expression recognition," IEEE Transactions on Image Processing, vol. 24, no. 1, pp. 189-204, 2014. https://doi.org/10.1109/TIP.2014.2375634
DOI
|
5 |
P. Hu, D. Cai, S. Wang, A. Yao, and Y. Chen, "Learning supervised scoring ensemble for emotion recognition in the wild," in Proceedings of the 19th ACM International Conference on Multimodal Interaction, Glasgow, UK, 2017, pp. 553-560.
|
6 |
J. Ueda and K. Okajima, "Face morphing using average face for subtle expression recognition," in Proceedings of 2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA), Dubrovnik, Croatia, 2019, pp. 187-192. https://doi.org/10.1109/ISPA.2019.8868931
DOI
|
7 |
N. P. Gopalan, S. Bellamkonda, and V. S. Chaitanya, "Facial expression recognition using geometric landmark points and convolutional neural networks," in Proceedings of 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), Coimbatore, India, 2018, pp. 1149-1153.
|
8 |
Y. He and X. He, "Facial expression recognition based on multi-feature fusion and HOSVD," in Proceedings of 2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China, 2019, pp. 638-643. https://doi.org/10.1109/ITNEC.2019.8729003
DOI
|
9 |
S. Wang, B. Pan, H. Chen, and Q. Ji, "Thermal augmented expression recognition," IEEE Transactions on Cybernetics, vol. 48, no. 7, pp. 2203-2214, 2018. https://doi.org/10.1109/TCYB.2017.2786309
DOI
|
10 |
Y. Fan, J. C. Lam, and V. O. Li, "Video-based emotion recognition using deeply-supervised neural networks," in Proceedings of the 20th ACM International Conference on Multimodal Interaction, Boulder, CO, 2018, pp. 584-588.
|
11 |
P. Liu, S. Han, Z. Meng, and Y. Tong, "Facial expression recognition via a boosted deep belief network," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, 2014, pp. 1805-1812. https://doi.org/10.1109/CVPR.2014.233
DOI
|
12 |
N. Song, H. Yang, and P. Wu, "A gesture-to-emotional speech conversion by combining gesture recognition and facial expression recognition," in Proceedings of 2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, 2018, pp. 1-6. https://doi.org/10.1109/ACIIAsia.2018.8470350
DOI
|