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Research Article
Computational Intelligence and Neuroscience
Volume 2018, Article ID 4967290, 1 page
https://doi.org/10.1155/2018/4967290
Corrigendum

Corrigendum to “A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks”

1Science and Technology on Parallel and Distributed Laboratory, National University of Defense Technology, Changsha, China
2College of Computer, National University of Defense Technology, Changsha, China

Correspondence should be addressed to Yuxing Peng; moc.nuyila@gnixuygnep

Received 3 July 2018; Accepted 24 July 2018; Published 12 September 2018

Copyright © 2018 Fangzhao Li et al. 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, and S. Jin, “A composite model of wound segmentation based on traditional methods and deep neural networks,” Computational Intelligence and Neuroscience, vol. 2018, Article ID 4149103, 12 pages, 2018. View at Publisher · View at Google Scholar