Employee Emotion Recognition Method Based on Improved MobileNetV3

DOI

10.2991/978-94-6463-638-3_18How to use a DOI?

Keywords

Employee Emotion Recognition Method; Improved MobileNetV3; facial expression recognition

Abstract

This paper has made improvements to the MobileNetV3 model, incorporating deep separable convolutions, inverted residual structures, and optimized time-consuming layer structures. Additionally, an improved attention mechanism has been proposed, utilizing a serial spatial channel attention mechanism. After multiple experiments, the improved model achieved an accuracy rate of 94.95% on the KDEF dataset, demonstrating that the enhancements have increased the accuracy of facial expression recognition.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Xi Chen
AU  - Miaoyun Hu
AU  - Xinle Zou
AU  - Yate Tan
PY  - 2024
DA  - 2024/12/30
TI  - Employee Emotion Recognition Method Based on Improved MobileNetV3
BT  - Proceedings of the 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024)
PB  - Atlantis Press
SP  - 180
EP  - 188
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-638-3_18
DO  - 10.2991/978-94-6463-638-3_18
ID  - Chen2024
ER  -