Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Correction

Correction: Recognition of mulberry leaf diseases based on multi-scale residual network fusion SENet

  • Chunming Wen,
  • Wangwang He,
  • Wanling Wu,
  • Xiang Liang,
  • Jie Yang,
  • Hongliang Nong,
  • Zimian Lan

The published funding statement is incorrect. The correct funding statement is as follows: This work was supported by the Key Laboratory of AI and Information Processing (Hechi University), Education Department of Guangxi Zhuang Autonomous Region (No. 2022GXZDSY009), Innovation Project of Guangxi Graduate Education (No. YCSW2022XXXX), College Student Innovation and Entrepreneurship Training Program (No. S202210608188X, No. 201810608082) and the Natural Science Foundation of Guangxi Province (No. 2018GXNSFAA281164). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Reference

  1. 1. Wen C, He W, Wu W, Liang X, Yang J, Nong H, et al. (2024) Recognition of mulberry leaf diseases based on multi-scale residual network fusion SENet. PLoS ONE 19(2): e0298700. https://doi.org/10.1371/journal.pone.0298700. pmid:38394274

Citation: Wen C, He W, Wu W, Liang X, Yang J, Nong H, et al. (2024) Correction: Recognition of mulberry leaf diseases based on multi-scale residual network fusion SENet. PLoS ONE 19(3): e0301490. https://doi.org/10.1371/journal.pone.0301490

Published: March 26, 2024

Copyright: © 2024 Wen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.