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Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Aboul Ella Hassanien,Siddhartha Bhattacharyya,Soum Conf

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31#
發(fā)表于 2025-3-26 23:03:23 | 只看該作者
Kenjiro Jimbo,Takayuki Kinoshita, the classified output is fed to the multi-layer perceptron for optimized output. In the evaluation, the proposed hybrid EB-MLP hybrid classifier achieved an accuracy of 92.3%, precision 92.4%, recall 87.4% and execution time 0.028?s. which outperformed other classifiers under analysis.
32#
發(fā)表于 2025-3-27 05:04:03 | 只看該作者
33#
發(fā)表于 2025-3-27 08:42:25 | 只看該作者
https://doi.org/10.1007/978-1-4613-0371-8e of various diabetic retinopathy and hypertensive retinopathy screening methodologies. The previously proposed techniques to detect hard exudates and retinal exudates are discussed in this present paper and the automated identification of hard exudates in hypertensive retinopathy is also discussed in the proposed paper.
34#
發(fā)表于 2025-3-27 09:45:43 | 只看該作者
35#
發(fā)表于 2025-3-27 15:53:25 | 只看該作者
Boundary Layer Flow and Its Dual Solutions Over a Stretching Cylinder: Stability Analysisl solutions exist due to stretching cylinder and there is an unexpected increase of heat at the surface of the cylinder. Stability analysis of dual solutions is implemented to characterize the linearly stable and physically realizable solution.
36#
發(fā)表于 2025-3-27 19:37:44 | 只看該作者
Mathematical Modelling of Power Law Fluid Flow Through a Pipe and Its Rheologyarameter and pressure drop in velocity and temperature distribution. Likewise, graphs are marked for the above profiles. It has been observed that pressure drop helps in reducing the shear stress. Also, as power law parameter increases, velocity decreases.
37#
發(fā)表于 2025-3-27 22:28:10 | 只看該作者
38#
發(fā)表于 2025-3-28 04:27:26 | 只看該作者
An Ensemble Deep Learning Method for Diabetes Mellitus, the classified output is fed to the multi-layer perceptron for optimized output. In the evaluation, the proposed hybrid EB-MLP hybrid classifier achieved an accuracy of 92.3%, precision 92.4%, recall 87.4% and execution time 0.028?s. which outperformed other classifiers under analysis.
39#
發(fā)表于 2025-3-28 08:08:22 | 只看該作者
40#
發(fā)表于 2025-3-28 14:16:53 | 只看該作者
Hard Exudates Detection: A Reviewe of various diabetic retinopathy and hypertensive retinopathy screening methodologies. The previously proposed techniques to detect hard exudates and retinal exudates are discussed in this present paper and the automated identification of hard exudates in hypertensive retinopathy is also discussed in the proposed paper.
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