Results 21 to 30 of about 265,367 (299)
Comparing the reliability of different ICA algorithms for fMRI analysis.
PLoS ONE, 2022 Independent component analysis (ICA) has been shown to be a powerful blind source separation technique for analyzing functional magnetic resonance imaging (fMRI) data sets.
Pengxu Wei, Ruixue Bao, Yubo Fan
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Applied Sciences, 2021 Dimensional reduction methods have significantly improved the simplification of Pulsed Thermography (PT) data while improving the accuracy of the results. Such approaches reduce the quantity of data to analyze and improve the contrast of the main defects
Julien R. Fleuret +3 more
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Nonlinear independent component analysis for principled disentanglement in unsupervised deep learning [PDF]
Patterns, 2023 Summary A central problem in unsupervised deep learning is how to find useful representations of high-dimensional data, sometimes called “disentanglement.” Most approaches are heuristic and lack a proper theoretical foundation.
Aapo Hyvärinen +2 more
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An Over-Complete Independent Component Analysis (ICA) Approach to Magnetic Resonance Image Analysis [PDF]
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005 This paper presents a new application of independent component analysis (ICA) in magnetic resonance (MR) image analysis. One of most successful applications for ICA-based approaches in MR imaging is functional MRI (fMRI) which basically deals with one-dimensional temporal signals.
Jing, Wang +5 more
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Frontiers in Human Neuroscience, 2013 In functional MRI it is desirable for the blood-oxygenation level dependent (BOLD) signal to be localized to the tissue containing activated neurons rather than the veins draining that tissue. This study addresses the dependence of the specificity of the
Alexander eGeissler +12 more
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Extraction of the underlying structure of systematic risk from non-Gaussian multivariate financial time series using independent component analysis: Evidence from the Mexican stock exchange [PDF]
, 2018 Regarding the problems related to multivariate non-Gaussianity of financial time series, i.e., unreliable results in extraction of underlying risk factors -via Principal Component Analysis or Factor Analysis-, we use Independent Component Analysis (ICA ...
Ladrón de Guevara Cortés, Rogelio +2 more
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Comparison of dimension reduction methods on fatty acids food source study
Scientific Reports, 2021 Serum fatty acids (FAs) exist in the four lipid fractions of triglycerides (TGs), phospholipids (PLs), cholesteryl esters (CEs) and free fatty acids (FFAs). Total fatty acids (TFAs) indicate the sum of FAs in them.
Yifan Chen +15 more
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Independent component approach to the analysis of EEG and MEG recordings [PDF]
, 2000 Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data ...
Hämäläinen, Dr Matti +4 more
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Sensors, 2012 Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the ...
Yiyu Zhou, Zhitao Huang, Xiang Wang
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Multiple-Exposure Image Fusion for HDR Image Synthesis Using Learned Analysis Transformations
Journal of Imaging, 2019 Modern imaging applications have increased the demand for High-Definition Range (HDR) imaging. Nonetheless, HDR imaging is not easily available with low-cost imaging sensors, since their dynamic range is rather limited.
Ioannis Merianos, Nikolaos Mitianoudis
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