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CORRECTION article

Front. Neurorobot., 10 November 2025

Volume 19 - 2025 | https://doi.org/10.3389/fnbot.2025.1711642

Correction: RSA-TransUNet: a robust structure-adaptive TransUNet for enhanced road crack segmentation

This article is a correction to:

  1. RSA-TransUNet: a robust structure-adaptive TransUNet for enhanced road crack segmentation

    1. Read original article
Liling HouLiling Hou1Fei Yu,, Fei Yu2,3,4*Yaowen HuYaowen Hu5Yang HuYang Hu6Ruoli YangRuoli Yang7
  • 1Zhangzhou Institute of Technology, Zhangzhou, China
  • 2College of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China
  • 3Key Lab of Light Field Manipulation and System Integration Applications in Fujian Province, School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China
  • 4Key Lab of Intelligent Optimization and Information Processing, Minnan Normal University, Zhangzhou, China
  • 5College of Computer Science and Technology, National University of Defense Technology, Changsha, China
  • 6College of Electronic Information and Physics, Central South University of Forestry and Technology, Changsha, China
  • 7College of Systems Engineering, National University of Defense Technology, Changsha, China

A Correction on
RSA-TransUNet: a robust structure-adaptive TransUNet for enhanced road crack segmentation

by Hou, L., Yu, F., Hu, Y., Hu, Y., and Yang, R. (2025). Front. Neurorobot. 19:1633697. doi: 10.3389/fnbot.2025.1633697

In the published article, in the Funding section, the funding sources “Education Research Project, JAT210843 and Zhangzhou Institute of Technology Project, ZZY2021b039 to Liling Hou” were erroneously omitted. The corrected Funding statement appears below:

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by Natural Science Foundation of Fujian Province (2024J01822); Natural Science Foundation of Zhangzhou City (ZZ2024J28); Education Research Project (JAT210843) and Zhangzhou Institute of Technology Project (ZZY2021b039) to Liling Hou.

The original version of this article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: road crack segmentation, axial-shift MLP attention, adaptive spline linear unit, structure-aware multi-stage, evolutionary optimization

Citation: Hou L, Yu F, Hu Y, Hu Y and Yang R (2025) Correction: RSA-TransUNet: a robust structure-adaptive TransUNet for enhanced road crack segmentation. Front. Neurorobot. 19:1711642. doi: 10.3389/fnbot.2025.1711642

Received: 23 September 2025; Accepted: 24 October 2025;
Published: 10 November 2025.

Approved by:

Frontier Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2025 Hou, Yu, Hu, Hu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Fei Yu, eXVmZWlAd2h1LmVkdS5jbg==

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.