Front. Artif. Intell., 01 September 2022
Sec. AI in Food, Agriculture and Water

Corrigendum: Poultry diseases diagnostics models using deep learning

  • 1Department of IT Systems Development and Management, Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania
  • 2Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, United States
  • 3Department of Computer Science and Engineering, University of Dar es Salaam, Dar es Salaam, Tanzania

A corrigendum on
Poultry diseases diagnostics models using deep learning

by Machuve, D., Nwankwo, E., Mduma, N., and Mbelwa, J. (2022). Front. Artif. Intell. 5:733345. doi: 10.3389/frai.2022.733345

In the published article, there was an error in the Funding statement. The funding statement did not use the text that is on the project agreement with the funder. The funding statement was displayed as: “The research project was funded by two grants: (1) The 2019 Early Career Fellowship Program of the Organization for Women in Science for the Developing World (OWSD) and (2) The International Development Research Center (IDRC) with IDRC Grant Number: 109187-002 through the 2020 IndabaX-AI4D Innovation Grant.”

The correct Funding statement appears below.


This work was carried out with the aid of a grant from UNESCO and the International Development Research Center, Ottawa, Canada. The views expressed herein do not necessarily represent those of UNESCO, IDRC, or its Board of Governors.

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: deep learning, agriculture, poultry disease diagnostics, dataset, image classification

Citation: Machuve D, Nwankwo E, Mduma N and Mbelwa J (2022) Corrigendum: Poultry diseases diagnostics models using deep learning. Front. Artif. Intell. 5:1016695. doi: 10.3389/frai.2022.1016695

Received: 11 August 2022; Accepted: 12 August 2022;
Published: 01 September 2022.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2022 Machuve, Nwankwo, Mduma and Mbelwa. 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: Dina Machuve,

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