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.
We now have our own terminal tournament featuring a competition for data scientists, analysts, and engineers. Trump mocks Biden and Obama for how they walk — and it reveals more than he realizes Top ...
Journal of Nuclear Medicine Technology August 2025, jnmt.125.269869; DOI: https://doi.org/10.2967/jnmt.125.269869 ...
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 ...
This paper shows that the Expectation-Maximization (EM) algorithm for regime-switching dynamic factor models provides satisfactory performance relative to other estimation methods and delivers a good ...
This repository provides tools and algorithms for the estimation of mixture models for mixed-type data. The algorithms jointly estimate the model parameters and the number of classes in the model.
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