Open Access Open Access  Restricted Access Subscription Access

An Expression Recognition Model Combining Attention and Residual Networks

Jiale Gu,
Xiaohong Jin,

Abstract


How to integrate multi-scale features and establish interdependencies between remote channels is a challenge for expression recognition networks. Based on this, the authors put forward a residual network on PSA (pyramid split attention)-ResNet, which replaces the 3 x 3 convolution in the ResNet50 residual module with PSA to draw multi-scale features and enhance the cross-channel information’s correlation availably. At the same time, to reduce the differences between similar expressions and expand the distance between different types of expressions, a joint loss function about Island Loss and SoftMax Loss has been introduced to optimize the parameters. The method proposed in this paper carried out simulation experiments with 2 datasets, Fer2013 and CK+, increasing precision rates to 74.26% and 98.35% respectively. This result further confirms that the method has yielded a great result on expression recognition compared with the cutting-edge algorithms.

Keywords


Pyramid split attention, Residual network, Channel attention, Group convolution

Citation Format:
Jiale Gu, Xiaohong Jin, "An Expression Recognition Model Combining Attention and Residual Networks," Journal of Internet Technology, vol. 26, no. 5 , pp. 703-711, Sep. 2025.

Full Text:

PDF

Refbacks

  • There are currently no refbacks.





Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
JIT Editorial Office, Office of Library and Information Services, National Dong Hwa University
No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien 974301, Taiwan, R.O.C.
Tel: +886-3-931-7314  E-mail: jit.editorial@gmail.com