Correction: Lin, Z.; Guo, W. Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models. Remote Sens. 2021, 13, 2822

Zhe Lin; Wenxuan Guo

doi:10.3390/rs14102313

and

¹

Department of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA

²

Department of Soil and Crop Sciences, Texas A&M AgriLife Research, Lubbock, TX 79403, USA

^*

Author to whom correspondence should be addressed.

Remote Sens.2022, 14(10), 2313;https://doi.org/10.3390/rs14102313

This article belongs to the Section Remote Sensing in Agriculture and Vegetation

Version Notes

Order Reprints

In the original publication [], there are two duplicated paragraphs in Section 3.2 on pages 8, 10, and 11, as published. The duplicated paragraphs under Table 2 should be removed and the position of Figures 3 and 4 should be updated accordingly.

The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original publication has also been updated.

Reference

Lin, Z.; Guo, W. Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models. Remote Sens. 2021, 13, 2822. [Google Scholar] [CrossRef]

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Correction: Lin, Z.; Guo, W. Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models. Remote Sens. 2021, 13, 2822

Reference

Article Metrics

Citations

Article Access Statistics