Graphical Abstract
![](https://wqketang.oss-cn-beijing.aliyuncs.com/zip-unzip/zip-460e934a-89cc-4d6f-aa74-7feadd4ee94d/101320TP-2024-3-593/files/101320TP-2024-3-593-gab.jpg?Expires=1725755358&OSSAccessKeyId=STS.NTb4DXU4JD36Bm7sCfLXpJ6m3&Signature=5qZXjCITNztnKqJHJps2Ipm8K84%3D&security-token=CAISywJ1q6Ft5B2yfSjIr5fXf%2F7suOtr8%2FHdQEuGl0MzQNdcpfPG0Tz2IHtKenhsBOsbtfk1mG5W5%2FgZlqJ9SptIAEfJa9d99MznDrFDltCT1fau5Jko1beHewHKeTOZsebWZ%2BLmNqC%2FHt6md1HDkAJq3LL%2Bbk%2FMdle5MJqP%2B%2FUFB5ZtKWveVzddA8pMLQZPsdITMWCrVcygKRn3mGHdfiEK00he8TouufTinpHMskGA1Aell7Mvyt6vcsT%2BXa5FJ4xiVtq55utye5fa3TRYgxowr%2Fwo0v0YpGya5YzHXwcPskvdKZbo78UqLQlla6w%2BGqFJqvPxr%2Fp8t%2Fx5fWJKAezhVgs8cVM8JOjIqKOscIsi5g%2Fq6gWPcD1LXoQ6vH1ZZ5%2FAzVZaVWUEMpNqcRxTMldXaQqhSZT8m3upKXzOJeX7ls9%2Fv%2FV7p7UvocvUTzDnGoABCKEw5zeqVEFt1P1tLtZPWFgqoxMOwG7QFDd16KVAW84FGRPy%2BnneCrZe0HYm786BcWDP3XmPmuNohvQFG%2FYf9X49aXiJQs6eJFt93A5NT8dSRXVX3d0gsHp4aPRQxBXChZPaPyC91ZpQadlfhy79dcqC4544nSt5yl%2BptAu%2FCNkgAA%3D%3D)
Discover the SciOpen Platform and Achieve Your Research Goals with Ease.
Recently, facial-expression recognition (FER) has primarily focused on images in the wild, including factors such as face occlusion and image blurring, rather than laboratory images. Complex field environments have introduced new challenges to FER. To address these challenges, this study proposes a cross-fusion dual-attention network. The network comprises three parts: (1) a cross-fusion grouped dual-attention mechanism to refine local features and obtain global information; (2) a proposed
276
Views
15
Downloads
2
Crossref
2
Web of Science
3
Scopus
0
CSCD
Altmetrics
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduc-tion 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 licence, and indicate if changes were made.
The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www.editorialmanager.com/cvmj.