This article is a correction to:
A meta-deep-learning framework for spatio-temporal underwater SSP inversion
Wei Huang
Deshi Li
Hao Zhang1- 1School of Electronic Engineering, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, China
- 2Electronic Information School, Wuhan University, Wuhan, China
- 3School of Space Science and Physics, Shandong University (Weihai), Weihai, China
- 4School of Science and Engineering, The Chinese University of Hong Kong (Shenzhen), Shenzhen, China
A Corrigendum on
A meta-deep-learning framework for spatio-temporal underwater SSP inversion
by Huang W, Li D, Zhang H, Xu T and Yin F (2023 Front. Mar. Sci. 10:1146333. doi: 10.3389/fmars.2023.1146333
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.
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: 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.
Edited and Reviewed by:
Hongsheng Bi, University of Maryland, College Park, United StatesCopyright © 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, eWluZmVuZ0BjdWhrLmVkdS5jbg==