A study on lightweight facial expression recognition based on enhanced network models

Xiaomei Lin; Wei Chen; Jian Fang; Haoran Sun

doi:10.1117/12.3055971

9 January 2025 A study on lightweight facial expression recognition based on enhanced network models

Xiaomei Lin, Wei Chen, Jian Fang, Haoran Sun

Author Affiliations +

Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 1348613 (2025) https://doi.org/10.1117/12.3055971
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China

Abstract

This paper introduces a neural network designed to be lightweight (DL) for face expression recognition using dilation convolution without increasing parameters, enabling efficient global feature extraction. Incorporating Leaky Relu mitigates gradient vanishing and enhances training robustness. Experiments show a 71% and 52% reduction in parameters for DL_Vgg19 and DL_ResNet34, respectively, with minimal accuracy loss, validating the method's efficiency.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Xiaomei Lin, Wei Chen, Jian Fang, and Haoran Sun "A study on lightweight facial expression recognition based on enhanced network models", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 1348613 (9 January 2025); https://doi.org/10.1117/12.3055971

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