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CORRECTION article

Front. Artif. Intell., 22 November 2023
Sec. AI in Food, Agriculture and Water
This article is part of the Research Topic Soft Computing and Machine Learning Applications for Healthcare Systems View all 10 articles

Corrigendum: mPD-APP: a mobile-enabled plant diseases diagnosis application using convolutional neural network toward the attainment of a food secure world

\r\nEmmanuel Oluwatobi Asani,&#x;Emmanuel Oluwatobi Asani1,2Yomi Phineas OsadeyiYomi Phineas Osadeyi1Adekanmi A. Adegun
Adekanmi A. Adegun3*Serestina Viriri
Serestina Viriri3*Joyce A. Ayoola&#x;Joyce A. Ayoola4Ebenezer Ayorinde KolawoleEbenezer Ayorinde Kolawole5
  • 1Department of Computer Science, Landmark University, Omu-Aran, Nigeria
  • 2Landmark University SDG 11 (Sustainable Cities and Communities Research Group), Omu-Aran, Nigeria
  • 3School of Mathematics, Statistics and Computer Science, University of Kwazulu-Natal, Durban, South Africa
  • 4Department of Electrical and Computer Engineering, Santa Clara University, Santa Clara, CA, United States
  • 5Department of Agricultural Economics and Extension, Landmark University, Omu-Aran, Nigeria

A corrigendum on
mPD-APP: a mobile-enabled plant diseases diagnosis application using convolutional neural network toward the attainment of a food secure world

by Asani, E. O., Osadeyi, Y. P., Adegun, A. A., Viriri, S., Ayoola, J. A., and Kolawole, E. A. (2023). Front. Artif. Intell. 6:1227950. doi: 10.3389/frai.2023.1227950

In the published article, there was an error in the email of one of the corresponding authors—Serestina Viriri. Instead of “virirs@ukzn.ac.za”, it should be “viriris@ukzn.ac.za”.

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: mobile-enabled, convolutional neural networks, diseases diagnosis system, SDG2, pathogens

Citation: Asani EO, Osadeyi YP, Adegun AA, Viriri S, Ayoola JA and Kolawole EA (2023) Corrigendum: mPD-APP: a mobile-enabled plant diseases diagnosis application using convolutional neural network toward the attainment of a food secure world. Front. Artif. Intell. 6:1325606. doi: 10.3389/frai.2023.1325606

Received: 21 October 2023; Accepted: 07 November 2023;
Published: 22 November 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 Asani, Osadeyi, Adegun, Viriri, Ayoola and Kolawole. 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: Adekanmi A. Adegun, adeguna@ukzn.ac.za; Serestina Viriri, viriris@ukzn.ac.za

ORCID: Emmanuel Oluwatobi Asani orcid.org/0000-0002-6774-8529
Joyce A. Ayoola orcid.org/0000-0003-0713-8128

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.