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. 2020 Jan 3;11:86. doi: 10.1038/s41467-019-13749-3

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — The training loss/accuracy (dim pink lines) and the validation loss/accuracy (deep pink lines) plotted as a function of the iteration number up to the 10th epoch for the CNN_2F (a, b), CNN_3F (c, d), CNN_4F (e, f), CNN_5F (g, h), and CNN_6F (i, j) architectures.