Results 41 to 50 of about 3,977,371 (295)
Halton Sampling for Image Registration Based on Mutual Information
, 2008 Mutual information is a widely used similarity measure for aligning multimodal medical images. At its core, it relies on the computation of a discrete joint histogram, which itself requires image samples for its estimation.
Michel Bierlaire +5 more
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Diabetes type 2 classification using machine learning algorithms with up-sampling technique
Journal of Electrical Systems and Information Technology, 2023 Recently, the rate of chronic diabetes disease has increased extensively. Diabetes increases blood sugar and other problems like blurred vision, kidney failure, nerve problems, and stroke.
Mariwan Ahmed Hama Saeed
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Empirical Characterization of Graph Sampling Algorithms
Social Network Analysis and Mining, 2022 Abstract Graph sampling allows mining a small representative subgraph from a big graph. Sampling algorithms deploy different strategies to replicate the properties of a given graph in the sampled graph. In this study, we provide a comprehensive empirical characterization of five graph sampling algorithms on six properties of a graph including ...
Muhammad Irfan Yousuf +2 more
openaire +2 more sources
Parameterized String Matching by Text Sampling
MathematicsString matching is a foundational problem in computer science with applications that span data mining, text retrieval, bioinformatics, and software engineering. Traditional string matching algorithms often face limitations with space and time efficiency,
Simone Faro +4 more
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Distributed Robust Algorithms with Dependent Sampling
MathematicsRobust algorithms have been widely used and intensively studied in the communities of engineering, statistics, and machine learning since such algorithms are less sensitive to outliers and effective in addressing the issue of non-Gaussian noise during ...
Baobin Wang, Ting Hu, Liangzhen Lei
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EvoPreprocess—Data Preprocessing Framework with Nature-Inspired Optimization Algorithms
Mathematics, 2020 The quality of machine learning models can suffer when inappropriate data is used, which is especially prevalent in high-dimensional and imbalanced data sets.
Sašo Karakatič
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EURASIP Journal on Advances in Signal Processing, 2021 In this paper, we address the problem of optimal measurement budget allocation to estimate the state of a linear discrete-time dynamical system over a finite horizon.
Antoine Aspeel +3 more
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Sparse Signal Representation, Sampling, and Recovery in Compressive Sensing Frameworks
IEEE Access, 2022 Compressive sensing allows the reconstruction of original signals from a much smaller number of samples as compared to the Nyquist sampling rate. The effectiveness of compressive sensing motivated the researchers for its deployment in a variety of ...
Irfan Ahmed +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Embryonal tumors comprise the majority of malignant central nervous system (CNS) neoplasms diagnosed in children under 3 years of age. Compared with their counterparts in older children, these tumors exhibit distinct molecular biology and a more aggressive clinical phenotype, while their management is complicated by the heightened ...
Sudarshawn Damodharan +3 more
wiley +1 more source
Parallel hierarchical sampling : a general-purpose class of multiple-chains MCMC algorithms [PDF]
, 2009 This paper introduces the Parallel Hierarchical Sampler (PHS), a class of Markov chain Monte Carlo algorithms using several interacting chains having the same target distribution but different mixing properties. Unlike any single-chain MCMC algorithm,
Mira, Antonietta +3 more
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