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. 2023 Jan 13;13:749. doi: 10.1038/s41598-023-27808-9

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© The Author(s) 2023

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Visual examples of pseudo label generation using teacher model $M_{T}$ that are used for training student model $M_{S}$ in conjunction with unlabelled data $D_{U}$ . It can be seen that $M_{T}$ has accurately predicted the pseudo labels for unlabelled images (it is also supported by the quantitative results).