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CORRECTION article

Front. Psychol., 23 May 2024
Sec. Emotion Science
This article is part of the Research Topic Exploring the Emotional Landscape: Cutting-Edge Technologies for Emotion Assessment and Elicitation View all 10 articles

Corrigendum: Music-evoked emotions classification using vision transformer in EEG signals

  • 1School of Intelligence Engineering, Shandong Management University, Jinan, China
  • 2School of Arts, Beijing Foreign Studies University, Beijing, China

A corrigendum on
Music-evoked emotions classification using vision transformer in EEG signals

by Wang, D., Lian, J., Cheng, H., and Zhou, Y. (2024). Front. Psychol. 15:1275142. doi: 10.3389/fpsyg.2024.1275142

In the published article, there was an error. It was not clearly denoted that authors Dong Wang and Jian Lian contributed equally to this work. The correct information is shown below.

Dong Wang1†, Jian Lian1†, Hebin Cheng1* and Yanan Zhou2*

These authors have contributed equally to this work

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: music-evoked emotion, emotion classification, electroencephalographic, deep learning, transformer

Citation: Wang D, Lian J, Cheng H and Zhou Y (2024) Corrigendum: Music-evoked emotions classification using vision transformer in EEG signals. Front. Psychol. 15:1422498. doi: 10.3389/fpsyg.2024.1422498

Received: 24 April 2024; Accepted: 13 May 2024;
Published: 23 May 2024.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2024 Wang, Lian, Cheng and Zhou. 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: Yanan Zhou, emhvdXlhbmFuJiN4MDAwNDA7YmZzdS5lZHUuY24=; Hebin Cheng, Y2hlbmdoZWJpbiYjeDAwMDQwO3NkbXUuZWR1LmNu

These authors have contributed equally to this work

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.