Corrigendum: Accurate few-shot object counting with Hough matching feature enhancement

He, Zhiquan; Zheng, Donghong; Wang, Hengyou

doi:10.3389/fncom.2023.1232762

CORRECTION article

Front. Comput. Neurosci., 20 June 2023

Volume 17 - 2023 | https://doi.org/10.3389/fncom.2023.1232762

This article is part of the Research Topic Machine-Learning/Deep-Learning methods in Neuromarketing and Consumer Neuroscience View all 9 articles

Corrigendum: Accurate few-shot object counting with Hough matching feature enhancement

This article is a correction to:

Accurate few-shot object counting with Hough matching feature enhancement
1. Read original article

$\r\nZhiquan He,$ Zhiquan He^1,2^*

Donghong Zheng²

Hengyou Wang³

¹Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China
²Guangdong Multimedia Information Service Engineering Technology Research Center, Shenzhen University, Shenzhen, China
³School of Science, Beijing University of Civil Engineering and Architecture, Beijing, China

A corrigendum on
Accurate few-shot object counting with Hough matching feature enhancement

by He, Z., Zheng, D., and Wang, H. (2023). Front. Comput. Neurosci. 17:1145219. doi: 10.3389/fncom.2023.1145219

In the published article, there was an error in the Funding statement.

Original text: This work was supported by the National Natural Science Foundation of China under Grants 61971290.

The Shenzhen City project support was missed by mistake. The correct Funding statement appears below.

This work was supported by the National Natural Science Foundation of China under grant 61971290, and the Shenzhen Stability Support General Project (Category A) 20200826104014001.

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: few-shot, object counting, Hough matching, feature enhancement, exemplar feature aggregation, self-attention

Citation: He Z, Zheng D and Wang H (2023) Corrigendum: Accurate few-shot object counting with Hough matching feature enhancement. Front. Comput. Neurosci. 17:1232762. doi: 10.3389/fncom.2023.1232762

Received: 01 June 2023; Accepted: 13 June 2023;
Published: 20 June 2023.

Approved by:

Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2023 He, Zheng and Wang. 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: Zhiquan He, zhiquan@szu.edu.cn

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.