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Titlebook: Communication and Intelligent Systems; Proceedings of ICCIS Harish Sharma,Mukesh Kumar Gupta,Wang Lipo Conference proceedings 2021 The Edit

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31#
發(fā)表于 2025-3-27 00:15:49 | 只看該作者
https://doi.org/10.1007/978-3-319-61518-9used for object and face recognition. By using a faster R-CNN model in money dataset training, we found about average 97.8% real-time accuracy. Our recognition accuracy was high compared with other state-of-the-art research work.
32#
發(fā)表于 2025-3-27 04:33:39 | 只看該作者
33#
發(fā)表于 2025-3-27 06:41:07 | 只看該作者
Identifying and Removing Software Cloness and approaches for the classification of documents using AI. Conclusions show that despite the challenges associated with the classification and categorization of documents, the applicability of AI techniques shows good results of accuracy to allow a better efficiency in the automation of RPA processes.
34#
發(fā)表于 2025-3-27 11:58:10 | 只看該作者
Neural Network Imitation Model of Realization of the Business Analysis Process,project from the received 25 scenarios. The article offers a mathematical description of the model and method for modeling these interactions from the perspective of game theory. This allows you to build appropriate formal models.
35#
發(fā)表于 2025-3-27 16:32:33 | 只看該作者
36#
發(fā)表于 2025-3-27 21:04:36 | 只看該作者
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Macimbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms.
37#
發(fā)表于 2025-3-28 01:47:56 | 只看該作者
A Comparative Analysis of Supervised Word Sense Disambiguation in Information Retrieval,ithms Na?ve Bayes, support vector machine (SMO), decision tree (J48), and KNN (IBK) through a series of experiments, and the result concludes that the algorithms performance is based on the features of the datasets.
38#
發(fā)表于 2025-3-28 04:31:03 | 只看該作者
39#
發(fā)表于 2025-3-28 07:34:40 | 只看該作者
40#
發(fā)表于 2025-3-28 14:14:19 | 只看該作者
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