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Python 3.5 TensorFlow 1.1.0 Keras 2.0.6 CUDA 8.0 cuDNN v5

This work was accepted to publish to International Conference on Pattern Recognition and Artificial Intelligence 2018 (ICPRAI 2018) http://www.icprai2018.com/

Facial Expression Recognition Using a Multi-level Convolutional Neural Network

Hai-Duong Nguyen*, Soonja Yeom**, Il-Seok Oh***, Kyoung-Min Kim****, Soo-Hyung Kim*
(*) School of Electronics and Computer Engineering, Chonnam National University, South Korea
(**) School of Engineering and ICT, University of Tasmania, Australia
(***) Department of Computer Science and Engineering, Chonbuk National University, South Korea
(****) Department of Electrical and Semiconductor Engineering, Chonnam National University, South Korea

@inproceedings{duong_icprai18,
  author        = "Nguyen, Hai-Duong and Yeom, Soonja and Oh, Il-Seok and Kim, Kyoung-Min and Kim, Soo-Hyung",
  title         = "Facial Expression Recognition Using a Multi-level Convolutional Neural Network",
  booktitle     = "Proceedings of International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI)",
  year          = "2018",
  pages         = "217--221"
}

and

@article{doi:10.1142/S0218001419400159,
  author = {Nguyen, Hai-Duong and Yeom, Soonja and Lee, Guee-Sang and Yang, Hyung-Jeong and Na, In-Seop and Kim, Soo-Hyung},
  title = {Facial Emotion Recognition Using an Ensemble of Multi-Level Convolutional Neural Networks},
  journal = {International Journal of Pattern Recognition and Artificial Intelligence},
  year = {2019},
  volume = {33},
  number = {8},
  month = Aug,
  url = {https://doi.org/10.1142/S0218001419400159},
  doi = {10.1142/S0218001419400159}
}

and

@ARTICLE{8863974,
  author={D. H. {Nguyen} and S. {Kim} and G. {Lee} and H. {Yang} and I. {Na} and S. H. {Kim}},
  journal={IEEE Transactions on Affective Computing},
  title={Facial Expression Recognition Using a Temporal Ensemble of Multi-level Convolutional Neural Networks},
  year={2019},
  doi={10.1109/TAFFC.2019.2946540}
}

Usage

  1. Download FER2013 testing set and save 2 npy files to the root folder
  2. Download trained MLCNN model
  3. Run fer2013_ensemble_mlcnns_testing_icprai2018.ipynb

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