Corrigendum: Small target detection with remote sensing images based on an improved YOLOv5 algorithm

In the published article, there was an error in Figure 12, Figure 13, and Table 5 as published. The descriptions at the bottom of the Figure 12 and Figure 13 were deleted. In addition, the resolution of all the figures in Table 5 was not high enough. The corrected Figure 12, Figure 13, and Table 5 and their captions appear 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.

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Figure 12. Comparison of the target detection of six different models on the Visdrone2019 dataset.

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Figure 13. Comparison of the target detection of six different models on the DIOR-VAS dataset.

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Table 5. Visual results of the small target detection on Visdrone2019 dataset.

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: small target detection, remote sensing images, YOLOv5s, deep learning, EIoU loss

Citation: Pei W, Shi Z and Gong K (2023) Corrigendum: Small target detection with remote sensing images based on an improved YOLOv5 algorithm. Front. Neurorobot. 17:1161652. doi: 10.3389/fnbot.2023.1161652

Received: 08 February 2023; Accepted: 13 February 2023;
Published: 28 February 2023.

Edited and reviewed by: Yimin Zhou, Shenzhen Institutes of Advanced Technology (CAS), China

Copyright © 2023 Pei, Shi and Gong. 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: Wenjing Pei, wenjingpei@buaa.edu.cn

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