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.