Research on a Lightweight Real-Time Facial Expression Recognition System Based on an Improved Mini-Xception Algorithm
Abstract
This paper proposes a lightweight facial expression recognition model based on an improved Mini-Xception algorithm to address the issue of deploying existing models on resource-constrained devices. The model achieves lightweight facial expression recognition, particularly for elder-oriented applications, by introducing depthwise separable convolutions, residual connections, and a four-class expression reconstruction. These designs significantly reduce the number of parameters and computational complexity while maintaining high accuracy. The model achieves an accuracy of 79.96% on the FER2013 dataset, outperforming various other popular models, and enables efficient real-time inference in standard CPU environments.
Fields of Study & Subjects
Emotion and Mood Recognition
Face and Expression Recognition
Advanced Computing and Algorithms
Publication details
- Journal / source
- Information
- Publisher
- MDPI AG
- Volume
- 17
- Issue
- 1
- Pages
- 111–111
- Publication date
- 22 January 2026
- Language
- EN