Skip to main content

CORRECTION article

Front. Plant Sci., 27 September 2023
Sec. Plant Bioinformatics
Volume 14 - 2023 | https://doi.org/10.3389/fpls.2023.1282443

Corrigendum: An advanced deep learning models-based plant disease detection: a review of recent research

This article is a correction to:

  1. An advanced deep learning models-based plant disease detection: A review of recent research

    1. Read original article
Muhammad Shoaib,&#x;Muhammad Shoaib1,2†Babar ShahBabar Shah3Shaker EI-Sappagh,Shaker EI-Sappagh4,5Akhtar AliAkhtar Ali6Asad UllahAsad Ullah2Fayadh AleneziFayadh Alenezi7Tsanko Gechev,Tsanko Gechev6,8Tariq Hussain*Tariq Hussain9*Farman Ali*&#x;Farman Ali10*†
  • 1Department of Computer Science, CECOS University of IT and Emerging Sciences, Peshawar, Pakistan
  • 2Department of Computer Science and Information Technology, Sarhad University of Science and Information Technology, Peshawar, Pakistan
  • 3College of Technological Innovation, Zayed University, Dubai, United Arab Emirates
  • 4Faculty of Computer Science and Engineering, Galala University, Suez, Egypt
  • 5Information Systems Department, Faculty of Computers and Artificial Intelligence, Benha University, Banha, Egypt
  • 6Department of Molecular Stress Physiology, Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
  • 7Department of Electrical Engineering, College of Engineering, Jouf University, Jouf, Saudi Arabia
  • 8Department of Plant Physiology and Molecular Biology, University of Plovdiv, Plovdiv, Bulgaria
  • 9School of Computer Science and Information Engineering, Zhejiang Gongshang University, Hangzhou, China
  • 10Department of Computer Science and Engineering, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, Republic of Korea

A Corrigendum on
An advanced deep learning models-based plant disease detection: a review of recent research

by Shoaib M, Shah B, EI-Sappagh S, Ali A, Ullah A, Alenezi F, Gechev T, Hussain T and Ali F (2023) Front. Plant Sci. 14:1158933. doi: 10.3389/fpls.2023.1158933

Incorrect affiliation

In the published article, there was an error in affiliation 10.

Instead of “Department of Software, Sejong University, Seoul, Republic of Korea”, it should be “Department of Computer Science and Engineering, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, Republic of Korea”.

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: machine learning, deep learning, plant disease detection, image processing, convolutional neural networks, performance evaluation, practical applications

Citation: Shoaib M, Shah B, EI-Sappagh S, Ali A, Ullah A, Alenezi F, Gechev T, Hussain T and Ali F (2023) Corrigendum: An advanced deep learning models-based plant disease detection: a review of recent research. Front. Plant Sci. 14:1282443. doi: 10.3389/fpls.2023.1282443

Received: 24 August 2023; Accepted: 29 August 2023;
Published: 27 September 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 Shoaib, Shah, EI-Sappagh, Ali, Ullah, Alenezi, Gechev, Hussain and Ali. 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: Farman Ali, ZmFybWFua2FuanVAc2Vqb25nLmFjLmty; Tariq Hussain, dW9tLnRhcmlxQGdtYWlsLmNvbQ==

†These authors have contributed equally to this work and share first authorship

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.