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. 2023 Jun 23;13:10221. doi: 10.1038/s41598-023-34795-4

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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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Performance per epoch for five-layer networks in HS3D dataset. Rows from top to bottom are for CNN, BLSTM, and extended BLSTM. Columns from left to right are (a) accuracy per epoch, (b) F1 score per epoch, and (c) A.U.C. Precision-Recall (PR), respectively. There is no indication of overfitting. All the training is completed successfully, and there is no gap between validation and training performance lines.