Research on Facial Expression Recognition Method Based on Improved ConvNeXt
ABSTRACT Advanced facial expression recognition technology can significantly enhance human‐computer interaction and improve intelligent services for humans. This paper introduces a novel facial expression recognition method utilizing an enhanced ConvNeXt network. By integrating the SENET attention mechanism into the ConvNeXt block, key feature information extraction is effectively enhanced. Additionally, the incorporation of the focal loss (FL) function optimizes the classification performance of the network model. Experimental results show that the improved ConvNeXt network achieves higher accuracy compared to other deep learning models, with accuracy rates of 83.8% and 70.4% on the RAF‐DB and FER2013 datasets, respectively.
Authors
- Xu Cheng (ORCID: https://orcid.org/0000-0002-5336-7952)
- Yu Cao (ORCID: https://orcid.org/0009-0006-7562-5680)
- Dan Chen (ORCID: https://orcid.org/0009-0007-2001-3334)
Institutions
- Shenyang Agricultural University (CN)
- Liaoning Shihua University (CN)
Publication Details
- Journal
- IET Image Processing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1049/ipr2.70118
- Primary Topic
- Emotion and Mood Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China