Results 11 to 20 of about 33,561,195 (290)
Neural KEM: A Kernel Method With Deep Coefficient Prior for PET Image Reconstruction. [PDF]
IEEE Trans Med Imaging, 2023 Image reconstruction of low-count positron emission tomography (PET) data is challenging. Kernel methods address the challenge by incorporating image prior information in the forward model of iterative PET image reconstruction. The kernelized expectation-
Li S +5 more
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Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method. [PDF]
J Biomed Opt, 2017 . Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals.
Baikejiang R +4 more
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Anatomically-aided PET reconstruction using the kernel method. [PDF]
Phys Med Biol, 2016 This paper extends the kernel method that was proposed previously for dynamic PET reconstruction, to incorporate anatomical side information into the PET reconstruction model.
Hutchcroft W +4 more
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PET image reconstruction using kernel method. [PDF]
IEEE Trans Med Imaging, 2015 Image reconstruction from low-count positron emission tomography (PET) projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality.
Wang G, Qi J.
europepmc +2 more sources
Journal of Taibah University for Science, 2019 In this work, the boundary layer flow of a Powell–Eyring non-Newtonian fluid over a stretching sheet has been investigated by a reproducing kernel method. Reproducing kernel functions are used to obtain the solutions.
Ali AKGÜL
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An optimal reproducing kernel method for linear nonlocal boundary value problems
Applied Mathematics Letters, 2018 F Z Geng
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Simplified reproducing kernel method for fractional differential equations with delay
Applied Mathematics Letters, 2016 Min-Qiang Xu, Yingzhen Lin
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A deep kernel method for lithofacies identification using conventional well logs
Petroleum Science, 2022 How to fi t a properly nonlinear classi fi cation model from conventional well logs to lithofacies is a key problem for machine learning methods. Kernel methods (e.g., KFD, SVM, MSVM) are effective attempts to solve this issue due to abilities of handling ...
Shaoqun Dong +7 more
semanticscholar +1 more source
, 2023 This chapter introduces a powerful class of machine learning approaches called kernel methods, which present an alternative to arguably more widely known neural network approaches. Kernel methods can learn even highly nonlinear problems by making an implicit transformation from a low-dimensional input space into a higher-dimensional feature space. This
Pinheiro Jr, Max, Dral, Pavlo
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Some error estimates for solving Volterra integral equations by using the reproducing kernel method
Journal of Computational and Applied Mathematics, 2015 R Mokhtari, E Babolian
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