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    An Ensemble Learning Approach for Facial Emotion Recognition Based on Deep Learning Techniques

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    ; Basel Vol. 14, Iss. 17,  (2025): 3415.     DOI:10.3390/electronics14173415
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    References (110)

    • 1.

      Excavating AI Re-excavated: debunking a fallacious account of the JAFFE dataset

      Lyons, M. .
    • 2.

      Google Colaboratory—Google

    • 3.

      Keras: The High-Level API for Tensorflow: Tensorflow Core. TensorFlow

      .
    • 4.

      Keras Documentation: Keras 3 API Documentation

      K. Team. .
    • 5.

      Machine Learning and Deep Learning for Emotion Recognition

      J. Sisquella Andrés. .
    • 6.

      Your Machine Learning and Data Science Community. Kaggle

      .
    • 7.

      Going deeper in facial expression recognition using deep neural networks

      Mollahosseini, A; Chan, D; Mahoor, M. 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
    • 8.

      Facial Expression Recognition Using Convolutional Neural Network with Data Augmentation

      Ahmed, T; Hossain, S; Hossain, M; Ul Islam, R; Andersson, K. 2019 Joint 8th International Conference on Informatics, Electronics & Vision (ICIEV) and 2019 3rd International Conference on Imaging, Vision & Pattern Recognition (icIVPR).
    • 9.

      Diabetic retinopathy diagnosis based on RA-efficientnet

      Yi, S; Yang, X; Wang, T; She, F; Xiong, X; He, J. Applied Sciences Vol. 11, Iss. 22, .
    • 10.

      A comparative analysis of eleven neural networks architectures for small datasets of lung images of COVID-19 patients toward improved clinical decisions

      Yang, Y; Zhang, L; Du, M; Bo, J; Liu, H; Ren, L; Li, X; Deen, MJ. Computers in Biology and Medicine Vol. 139, .
    • 11.

      AffectNet: a database for facial expression, valence, and arousal computing in the wild

      Mollahosseini, A; Hasani, B; Mahoor, M. IEEE Trans. Affect. Comput Vol. 10, Iss. 1, .
    • 12.

      Training deep networks for facial expression recognition with crowd-sourced label distribution

      Barsoum, E; Zhang, C; Ferrer, C; Zhang, Z. International Conference on Multimodal Interact.
    • 13.

      Emotion recognition from facial expression using deep convolutional neural network

      Liliana, D. J. Phys.: Conf. Ser Vol. 1193, .
    • 14.

      Constants across cultures in the face and emotion

      Ekman, P; Friesen, W. J. Pers. Soc. Psychol Vol. 17, Iss. 2, .
    • 15.

      FERA 2015—Second Facial Expression Recognition and Analysis Challenge

      M.F. Valstar; T. Almaev; J.M. Girard; G. McKeown; M. Mehu; L. Yin; M. Pantic; J.F. Cohn. Proceedings of the 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) Vol. Volume 6, .
    • 16.

      Gabor Wavelets in Image Processing

      D. Bařina. Proceedings of the 17th Conference STUDENT EEICT 2011.
    • 17.

      The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression

      P. Lucey; J.F. Cohn; T. Kanade; J. Saragih; Z. Ambadar; I. Matthews. Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops.
    • 18.

      Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark

      A. Dhall; R. Goecke; S. Lucey; T. Gedeon. Proceedings of the 2011 IEEE International Conference on Computer Vision Workshops (ICCV workshops).
    • 19.

      Using Kinect for face recognition under varying poses, expressions, illumination and disguise

      B.Y.L. Li; A.S. Mian; W. Liu; A. Krishna. Proceedings of the 2013 IEEE Workshop on Applications of Computer Vision (WACV): 186-192.
    • 20.

      Facial Action Units Intensity Estimation by the Fusion of Features with Multi-kernel Support Vector Machine

      Z. Ming; J. Rouas; T. Shochi. Proceedings of the 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG) Vol. Volume 6, : 1-6.