Text correction
In the published article, there was an error. The subscript on the numerator and denominator in formula 2 was written backwards.
A correction has been made to Preliminary, Signal propagation time simulation, Paragraph 2. This sentence previously stated:
The corrected sentence appears below:
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.
Statements
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
sound speed profile (SSP) inversion, artificial neural networks (ANN), few-shot learning, task-driven meta-learning (TDML), over-fitting effect
Citation
Huang W, Li D, Zhang H, Xu T and Yin F (2023) Corrigendum: A meta-deep-learning framework for spatio-temporal underwater SSP inversion. Front. Mar. Sci. 10:1321121. doi: 10.3389/fmars.2023.1321121
Received
13 October 2023
Accepted
19 October 2023
Published
26 October 2023
Volume
10 - 2023
Edited and reviewed by
Hongsheng Bi, University of Maryland, College Park, United States
Updates
Copyright
© 2023 Huang, Li, Zhang, Xu and Yin.
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: Feng Yin, yinfeng@cuhk.edu.cn
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.