The dataset referred to as the IPPN dataset (p. 4) in the original article is now referred to by its authors as the PRL dataset1. This dataset was used because it includes annotations for all three of the tasks performed in the validation experiments2. In the results on the leaf counting task (Table 2), the proposed method was compared against two results from the literature. However, the results reported in the cited papers were performed on a different version of the dataset, which is referred to by its authors as CVPPP 2015_LCC (for the leaf counting competition of the 2015 Computer Vision Problems in Plant Phenotyping workshop). Therefore, the direct comparison is not warranted. However, R2 between the actual and predicted leaf counts for the Plant/Ara2012, Plant/Ara2013-Canon, and Plant/Tobacco leaf counting datasets as presented in the article are 0.85, 0.90, and 0.74, respectively, demonstrating strong performance without the context of this comparison. This error does not change the scientific conclusions of the article in any way.
Statements
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Footnotes
1.^https://www.plant-phenotyping.org/datasets-home.
2.^Datasets A1, A2, and A3 in the original article refer to datasets Plant/Ara2012, Plant/Ara2013-Canon, and Plant/Tobacco, respectively in the PRL data.
Summary
Keywords
phenotyping, deep learning, methods, computer vision, machine learning
Citation
Ubbens JR and Stavness I (2018) Corrigendum: Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks. Front. Plant Sci. 8:2245. doi: 10.3389/fpls.2017.02245
Received
12 October 2017
Accepted
20 December 2017
Published
15 January 2018
Volume
8 - 2017
Edited and reviewed by
Roger Deal, Emory University, United States
Updates
Copyright
© 2018 Ubbens and Stavness.
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) or licensor 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: Ian Stavness ian.stavness@usask.ca
This article was submitted to Technical Advances in Plant Science, a section of the journal Frontiers in Plant Science
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