- 1University of Shanghai for Science and Technology, Institute of Machine Intelligence, Shanghai, China
- 2Origin Dynamics Intelligent Robot Co., Ltd., Zhengzhou, China
A Correction on
Multi-label remote sensing classification with self-supervised gated multi-modal transformers
by Liu, N., Yuan, Y., Wu, G., Zhang, S., Leng, J., and Wan, L. (2024). Front. Comput. Neurosci. 18:1404623. doi: 10.3389/fncom.2024.1404623
In the published article, there was an error in the Funding statement. The Funding statement was erroneously omitted, and financial support grants should have instead been included. The correct 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 the National key Research and Development plan of Ministry of Science and Technology of China (Grant Nos. 2023YFC3605800 and 2023YFC3605803) and the Henan Provincial Key Research and Development Program, China (Grant No. 251111220500).
The original article has been updated.
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Keywords: self-supervised learning, pre-training, vision transformer, multi-modal, gated units
Citation: Liu N, Yuan Y, Wu G, Zhang S, Leng J and Wan L (2025) Correction: Multi-label remote sensing classification with self-supervised gated multi-modal transformers. Front. Comput. Neurosci. 19:1665406. doi: 10.3389/fncom.2025.1665406
Received: 14 July 2025; Accepted: 01 August 2025;
Published: 18 August 2025.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2025 Liu, Yuan, Wu, Zhang, Leng and Wan. 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: Lihong Wan, bGh3YW45MTdAMTYzLmNvbQ==