CORRECTION article

Front. Environ. Sci., 27 May 2025

Sec. Environmental Informatics and Remote Sensing

Volume 13 - 2025 | https://doi.org/10.3389/fenvs.2025.1621083

Corrigendum: Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring

  • 1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

  • 2. School of Electronic, Electrical and CommunicationEngineering, University of Chinese Academy of Sciences, Beijing, China

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In the published article, there was an error in the Funding statement. The authors inadvertently omitted a funding source: The Science and Disruptive Technology Project of Aerospace Information Research Institute, Chinese Academy of Sciences (Grant No. E2Z206010F). The correct Funding statement appears below.

Statements

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the National Natural Science Foundation of China: 42071413, and the Science and disruptive technology project of Aerospace Information Research Institute of Chinese Academy of Sciences, grant number E2Z206010F.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original 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.

Summary

Keywords

remote sensing sample datasets, remote sensing sample retrieval, remote sensing sample database, AI-enabled remote sensing application, remote sensing imagery, deep learning, label category system, remote sensing big data

Citation

Ren X, Ma Y and Zhou Y (2025) Corrigendum: Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring. Front. Environ. Sci. 13:1621083. doi: 10.3389/fenvs.2025.1621083

Received

30 April 2025

Accepted

01 May 2025

Published

27 May 2025

Approved by

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

13 - 2025

Updates

Copyright

*Correspondence: Yan Ma,

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.

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