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Titlebook: Intelligent Systems and Data Science; First International Nguyen Thai-Nghe,Thanh-Nghi Do,Peter Haddawy Conference proceedings 2024 The Edi

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Transliterating Nom Script into Vietnamese National Script Using Multilingual Neural Machine Translas a significant improvement of +6.3 BLEU score compared to the NMT baseline. We also conduct preliminary experiments on incorporating BERT-NMT into multilingual machine translation to enhance the performance of low-resource translation tasks in general.
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The Efficiency of Japanese Character Classification by Attention Mechanismfrom the previous layers of the model. After changing the Vanilla CNN backbone to Residual CNN, the model included 3.8M parameters and achieved an accuracy rate of 99.08% and 98.11% on the test set of the 10-class and 49-class, respectively. In addition, the Grad-CAM method is used to improve the explanatory power of how the model makes decisions.
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Improved Gene Expression Classification Through Multi-class Support Vector Machines Feature Selectio classification results for high-dimensional gene expression datasets. Empirical test results on 25 gene expression datasets show that our multi-class SVM eliminates 99% of full dimensions, resulting in 7.1%, 4.03% increase in accuracy compared to training SVM, random forest models on the full dimensions of gene expression datasets, respectively.
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development occurs in the liver, then the focus shifts to the spleen and subsequently to the bone marrow (see review by M. 1979). The possibility that Peyer’s patches (PPs) also contribute to early B-cell ontogeny has been the topic of a number of studies, particularly in the late 1960s when the ro
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