Results 151 to 160 of about 708,932 (315)
Application of kernel-based Bayesian optimization in 3D CZT SPECT reconstructions [PDF]
openApplication of kernel-based Bayesian optimization in 3D CZT SPECT reconstructionsApplication of kernel-based Bayesian optimization in 3D CZT SPECT ...
PASTRELLO, LUCA
core
On Determination Method for Resolution of Secondary Electron Images in Scanning Electron Microscopy
Advanced Science, EarlyView.An idealized SEM, termed Rayleigh's microscope, is constructed by Monte Carlo simulation to represent imaging conditions that just satisfy the Rayleigh criterion. Based on this physically defined model, sharpness–resolution conversion curves are established and combined with the Rose criterion, enabling automated resolution evaluation from practical ...
Tongfang Yang, Yanbo Zou, Zejun Ding
wiley +1 more source
On the Eigenspectrum of the Gram matrix and the generalisation error of kernel PCA [PDF]
, 2004 In this paper we analyze the relationships between the eigenvalues of the m x m Gram matrix K for a kernel k(.,.) corresponding to a sample x1,...,xm drawn from a density p(x) and the eigenvalues of the corresponding continuous eigenproblem. We bound the
Shawe-Taylor, John +3 more
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MetabolitesBackground/Objectives: The physiological disorder known as “orange spot” in Juglans regia L. cv. Chandler is an emerging kernel quality issue of increasing concern for the Chilean walnut industry.
Ignacia Hernández +6 more
doaj +1 more source
Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
wiley +1 more source
sparr: Analyzing Spatial Relative Risk Using Fixed and Adaptive Kernel Density Estimation in R [PDF]
The estimation of kernel-smoothed relative risk functions is a useful approach to examining the spatial variation of disease risk. Though there exist several options for performing kernel density estimation in statistical software packages, there have ...
Tilman M. Davies +2 more
core +1 more source
Advanced Science, EarlyView.A biotin‐modified artificial insertion peptide functionalized three‐dimensional high‐curvature‐TiO2 nano‐interface was engineered in a microfluidic chip to improve the isolation efficiency of small extracellular vesicles (sEVs). This chip balanced affinity, releasability, and extendibility, enabling high‐throughput recovery of sEVs for downstream ...
Le Wang +7 more
wiley +1 more source
CoRRThe use of kernels for nonlinear prediction is widespread in machine learning. They have been popularized in support vector machines and used in kernel ridge regression, amongst others. Kernel methods share three aspects. First, instead of the original matrix of predictor variables or features, each observation is mapped into an enlarged feature space.
Patrick J. F. Groenen, Michael Greenacre
openaire +2 more sources
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source