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Titlebook: Nature of Computation and Communication; 7th EAI Internationa Phan Cong Vinh,Nguyen Huu Nhan Conference proceedings 2021 ICST Institute for

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樓主: Fixate
21#
發(fā)表于 2025-3-25 05:55:34 | 只看該作者
Improving Morphology and Recurrent Residual Refinement Network to Classify Hypertension in Retinal retinal blood vessel segmentation is one of the state-of-the-art approaches. Therefore, the detection and classification of hypertensive retinal images is very useful in the diagnosis of hypertension. This paper proposed a method for the hypertension classification based on saliency, in which the e
22#
發(fā)表于 2025-3-25 08:23:37 | 只看該作者
,The Impacts of?the?Contextual Substitutions in?Vietnamese Micro-text Augmentation,verfitting. However, the annotated dataset is unavailable, especially for the low resource languages. Building them is a tedious, time-consuming and expensive task. Thus, data augmentation has been mentioned as a perfect approach to generate the annotated data from the limited data without user inte
23#
發(fā)表于 2025-3-25 12:41:48 | 只看該作者
24#
發(fā)表于 2025-3-25 18:24:27 | 只看該作者
25#
發(fā)表于 2025-3-25 22:40:25 | 只看該作者
26#
發(fā)表于 2025-3-26 03:29:36 | 只看該作者
27#
發(fā)表于 2025-3-26 05:34:24 | 只看該作者
28#
發(fā)表于 2025-3-26 08:55:37 | 只看該作者
An Improved Algorithm to Protect Sensitive High Utility Itemsets in Transaction Database, transaction databases from being exploited by data mining techniques. This paper studies methods to hide sensitive high utility itemsets in transaction databases. There are some effective methods to deal with this problem, but these methods still cause undesirable side effects, such as: being missi
29#
發(fā)表于 2025-3-26 14:40:56 | 只看該作者
30#
發(fā)表于 2025-3-26 17:49:22 | 只看該作者
Predicting Vietnamese Stock Market Using the Variants of LSTM Architecture,rket prediction. However, achieving good results in prediction is still a challenge in research and there are very few studies applied to Vietnamese stock market data. Therefore, it is necessary to improve or introduce new forms of prediction. Specifically, we have focused on the stock prediction pr
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