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Titlebook: Intelligent Sustainable Systems; Proceedings of ICISS Jennifer S. Raj,Ram Palanisamy,Yong Shi Conference proceedings 2022 The Editor(s) (if

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发表于 2025-3-26 21:45:21 | 显示全部楼层
,Deep Learning-Based Approach for Parkinson’s Disease Detection Using Region of Interest,he same, deep learning-based classification of brain MRI at the subject level is the requirement in the medical field. In this work, we have implemented an algorithm to identify the most discriminative range of MRI slices at the subject level to differentiate between Normal Cohorts (NC) and Parkinso
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Classification of Class-Imbalanced Diabetic Retinopathy Images Using the Synthetic Data Creation bylication results in loss of eyesight if not diagnosed in the early stages. There are five stages of diabetic retinopathy: No DR, mild, moderate, severe, and proliferative. DR detection by traditional methods consumes a lot of time. An automatic and precise model would require an adequate amount of d
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CloudML: Privacy-Assured Healthcare Machine Learning Model for Cloud Network,oud has seen fastest adoption in the industry. The popularity of cloud is closely linked to the benefits it offers which ranges from a group of stakeholders to huge number of entrepreneurs. This enables some prominent features such as elasticity, scalability, high availability, and accessibility. So
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Multi-objective Optimization for Dimension Reduction for Large Datasets,r area of concern with application of machine learning algorithms. Therefore, it is considered to be a complicated task to handle and perform computation on such large, complex, and heterogenous dataset. In this paper, a brief discussion about different dimension reduction or feature selection algor
发表于 2025-3-28 08:22:47 | 显示全部楼层
Modified Leader Algorithm for Under-Sampling the Imbalanced Dataset for Classification,samples in one class is more in number than the other class, namely, imbalanced, then the performance of a classifier gets degraded due to the limited availability of the training instances in a particular class. To overcome the problems with the imbalanced datasets, a new under-sampling method has
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Weather Divergence of Season Through Regression Analytics,es obtain an obvious report of the prediction of weather. In our perspective, research is performed through many previous datasets in the weather forecast. Incorporating a model of multilinear regression and quantile regression allows visualizing the previous data to analyze the weather prediction.
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