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This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

In the article titled “A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks” [1], the first affiliation was incomplete. The revised affiliations’ list is shown above.

References

[1] F. Li, C. Wang, X. Liu, Y. Peng, S. Jin, "A composite model of wound segmentation based on traditional methods and deep neural networks," Computational Intelligence and Neuroscience, vol. 2018,DOI: 10.1155/2018/4149103, 2018.

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Copyright © 2018 Fangzhao Li et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0/

Details

Title
Corrigendum to “A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks”
Author
Li, Fangzhao 1   VIAFID ORCID Logo  ; Wang, Changjian 2 ; Liu, Xiaohui 1 ; Peng, Yuxing 1   VIAFID ORCID Logo  ; Jin, Shiyao 1 

1  Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Changsha, China 
2  College of Computer, National University of Defense Technology, Changsha, China 
Publication year
2018
Publication date
2018
Publisher
John Wiley & Sons, Inc.
ISSN
16875265
e-ISSN
16875273
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1155/2018/4967290
ProQuest document ID
2111095495
Copyright
Copyright © 2018 Fangzhao Li et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. http://creativecommons.org/licenses/by/4.0/