Abstract
Since the deep learning methods used in current face recognition do not balance well between recognition rate and recognition speed, the present work proposed a face expression recognition model based on multilayer feature fusion with lightweight convolutional networks. The model is tested on two commonly used real expression datasets, FER- 2013 and AffectNet, the accuracy of ms_model_M is 74.35% and 56.67%, respectively, and the accuracy of the traditional MovbliNet model is 74.11% and 56.48% in the tests of these two datasets.
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CITATION STYLE
Chen, Y., & He, J. (2022). Deep Learning-Based Emotion Detection. Journal of Computer and Communications, 10(02), 57–71. https://doi.org/10.4236/jcc.2022.102005
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