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Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Paramartha Dutta,Satyajit Chakrabarti,Celia Shahna Conf

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樓主: 大腦
11#
發(fā)表于 2025-3-23 13:27:19 | 只看該作者
Nonclassical Nonlinear Acoustical Imaging,e usage of multiple technologies like Artificial Intelligence, Machine Learning, Data Mining methods, etc., there is a need to provide proper security to the IoT system also. Several layers used in the IoT architecture need to be protected. Hence, there is a need to make a robust system in order to
12#
發(fā)表于 2025-3-23 14:11:17 | 只看該作者
13#
發(fā)表于 2025-3-23 21:18:59 | 只看該作者
Nonlinear Analysis of Physiological Data quantitative parameters, i.e., .. The presented approach is thoroughly compared with the state of the art and advanced changed detection approaches and found that the proposed method is superior in numerous ways.
14#
發(fā)表于 2025-3-24 01:37:20 | 只看該作者
Roll Model Control of Autonomous Vehiclere done. The data was split for training and testing and the score of the model obtained on the test dataset was 0.9691. The startup profit predictor was successfully built using random forest regressor model and it can be used for making profit predictions with 96.91% accuracy.
15#
發(fā)表于 2025-3-24 04:36:08 | 只看該作者
16#
發(fā)表于 2025-3-24 06:41:39 | 只看該作者
17#
發(fā)表于 2025-3-24 13:02:21 | 只看該作者
https://doi.org/10.1007/978-3-031-15207-8hanges its behaviour. Pests are also a major problem. Image Processing has evolved as an effective thing for the early analysis and detection of plant disease. Several algorithms have used to analyze the diseases at the early stage that results in minimum loss to the farmers and good quality of crop
18#
發(fā)表于 2025-3-24 17:20:42 | 只看該作者
https://doi.org/10.1007/978-3-662-04299-1from initial symptoms and information like fever, cough, sore throat using machine learning algorithms. The study includes working with six predicting models, MLP, GBC, Decision tree, SVM, Logistic Regression and Random forest with highest accuracy of 92.94% achieved in logical regression. The resul
19#
發(fā)表于 2025-3-24 21:20:55 | 只看該作者
20#
發(fā)表于 2025-3-25 00:39:35 | 只看該作者
Analysis of Tide Gauge Sea Level Time Seriesnd their related visible imperceptibility metrics that use a portion of the graphic. For output enhancement, the learned model is further utilized. To surpass the current innovative frameworks, the proposed model is shown.
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