Emotion Detection Using Deep Fusion Model
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-31164-2_40
Reference20 articles.
1. Do, L.-N., Yang, H.-J., Nguyen, H.-D., Kim, S.-H., Lee, G.-S., Na, I.-S.: Deep neural network-based fusion model for emotion recognition using visual data. J. Supercomput. 77(10), 10773–10790 (2021). https://doi.org/10.1007/s11227-021-03690-y
2. Liu, Y., Guo, Y., Georgiou, T., Lew, M.S.: Fusion that matters: convolutional fusion networks for visual recognition. Multimedia Tools Appl. 77(22), 29407–29434 (2018). https://doi.org/10.1007/s11042-018-5691-4
3. Aza, M.F.U., Suciati, N., Hidayati, S.C.: Performance study of facial expression recognition using convolutional neural network. In: 2020 6th International Conference on Science in Information Technology (ICSITech), pp. 121–126. IEEE (2020)
4. Ercolano, G., Rossi, S.: Combining CNN and LSTM for activity of daily living recognition with a 3D matrix skeleton representation. Intel. Serv. Robot. 14(2), 175–185 (2021). https://doi.org/10.1007/s11370-021-00358-7
5. Jaiswal, A., Raju, A. K., Deb, S.: Facial emotion detection using deep learning. In: 2020 International Conference for Emerging Technology (INCET), pp. 1–5. IEEE (2020)
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