The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...
ABSTRACT: Aiming at the problems of intensity inhomogeneity, boundary blurring and noise interference in the segmentation of three-dimensional volume data (such as medical images and industrial CT ...
Abstract: This article proposes an expectation maximization sample transfer identification (EM-STI) algorithm to address the parameter identification problem in dynamic systems with nonideal data.
From public health campaigns to information about social services, algorithms that identify “influencers” have been used to maximize reach. Vedran Sekara and colleagues used the independent cascade ...
Division of Intramural Research, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States ...
ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...
In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...
Recently, there has been a growing literature exploring the generalization of quantum algorithms, such that different quantum algorithms are special examples of a more fundamental structure. In this ...
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