CORRECTION article

Front. Plant Sci., 21 December 2022

Sec. Sustainable and Intelligent Phytoprotection

Volume 13 - 2022 | https://doi.org/10.3389/fpls.2022.1092374

Corrigendum: Improved YOLOv4 recognition algorithm for pitaya based on coordinate attention and combinational convolution

  • 1. College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China

  • 2. Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province, Henan University of Science and Technology, Luoyang, China

  • 3. School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China

  • 4. Key Laboratory of Modern Agricultural Equipment and Technology of Ministry of Education, Jiangsu University, Zhenjiang, China

  • 5. College of Physical Engineering, Henan University of Science and Technology, Luoyang, China

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In the published article, there was an error in Figure 2 as published. An error appears in the upper left corner of the figure. The corrected Figure 2 and its caption YOLOv4 network structure diagram. * means repeat the operation. appear below.

Figure 2

In the published article, there was an error in Figure 6 as published. The left side of the figure is missing. The corrected Figure 6 and its caption Improved combinational convolution-CA module at fusion. appear below.

Figure 6

In the published article, there was an error in Figure 10 as published. An error appears in the upper left corner of the figure. The corrected Figure 10 and its caption The improved YOLOv4 network structure diagram. * means repeat the operation. appear below.

Figure 10

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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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

improved YOLOv4, GhostNet, coordinate attention, improved combinational convolution module, target recognition

Citation

Zhang F, Cao W, Wang S, Cui X, Yang N, Wang X, Zhang X and Fu S (2022) Corrigendum: Improved YOLOv4 recognition algorithm for pitaya based on coordinate attention and combinational convolution. Front. Plant Sci. 13:1092374. doi: 10.3389/fpls.2022.1092374

Received

08 November 2022

Accepted

06 December 2022

Published

21 December 2022

Volume

13 - 2022

Edited and reviewed by

Yongliang Qiao, The University of Sydney, Australia

Updates

Copyright

*Correspondence: Ning Yang, ; Sanling Fu,

This article was submitted to Sustainable and Intelligent Phytoprotection, a section of the journal Frontiers in Plant Science

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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