This article is a correction to:
Improved YOLOv4 recognition algorithm for pitaya based on coordinate attention and combinational convolution
Fu Zhang
Weihua Cao1
Ning Yang
Xiaodong Zhang
Sanling Fu- 1College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China
- 2Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province, Henan University of Science and Technology, Luoyang, China
- 3School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China
- 4Key Laboratory of Modern Agricultural Equipment and Technology of Ministry of Education, Jiangsu University, Zhenjiang, China
- 5College of Physical Engineering, Henan University of Science and Technology, Luoyang, China
A corrigendum on
Improved YOLOv4 recognition algorithm for pitaya based on coordinate attention and combinational convolution
by Zhang F, Cao W, Wang S, Cui X, Yang N, Wang X, Zhang X and Fu S (2022) 13:1030021. doi: 10.3389/fpls.2022.1030021
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
Figure 2 YOLOv4 network structure diagram. * means repeat the operation.
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
Figure 6 Improved combinational convolution-CA module at fusion.
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
Figure 10 The improved YOLOv4 network structure diagram. * means repeat the operation.
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: 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.
Edited and Reviewed by:
Yongliang Qiao, The University of Sydney, AustraliaCopyright © 2022 Zhang, Cao, Wang, Cui, Yang, Wang, Zhang and Fu. 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: Ning Yang, eWFuZ25AdWpzLmVkdS5jbg==; Sanling Fu, ZnVzYW5saW5nQDEyNi5jb20=