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  • Correction
  • Open Access

Correction to: Detection and analysis of wheat spikes using Convolutional Neural Networks

Plant Methods201915:27

https://doi.org/10.1186/s13007-019-0405-0

  • Published:

The original article was published in Plant Methods 2018 14:100

Correction to: Plant Methods (2018) 14:100 https://doi.org/10.1186/s13007-018-0366-8

In the original publication of this article [1] the authors stated that important resources would be made available online to readers. Unfortunately, due to an error on the authors' behalf, a link to those resources was not included in the final version of the manuscript.

The SPIKE dataset, including images of wheat spikes and labelled bounding boxes for individual spikes, as well as the four trained CNN models described in the article, can now be found at the following sourceforge page:

https://sourceforge.net/projects/spike-dataset/

The link provides access to the free download of all images used in the article as well as their ground truth labelling. The four CNN models available for download at the sourceforge link are to be used in conjunction with the microsoft cognitive toolkit, available at:

https://docs.microsoft.com/en-gb/cognitive-toolkit/

Finally, an additional more user-friendly program has also been uploaded to the sourceforge page. This program contains the same functionality as is currently available through the cognitive toolkit. However, the user will be able to quickly and easily select a dataset of their own images and run the models for spike detection, without downloading and installing the cognitive toolkit.

Notes

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Phenomics and Bioinformatics Research Centre, University of South Australia, Mawson Lakes, Adelaide, 5095, Australia
(2)
School of Engineering and Information Technology, Murdoch University, Perth, Western Australia, 6150, Australia

Reference

  1. Hasan Md, et al. Detection and analysis of wheat spikes using Convolutional Neural Networks. Plant Methods. 2018;14:100. https://doi.org/10.1186/s13007-018-0366-8.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© The Author(s) 2019

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