Results 241 to 250 of about 665,590 (295)

Near-Infrared Hyperspectral Imaging for Non-Destructive Detection of Old Rice in Freshly Milled Rice. [PDF]

Foods
Workhwa S, Suwapanich R, Sahachairungrueng W, Thompson AK, Teerachaichayut S.   +4 more
europepmc   +1 more source

Lightweight and Robust Radar Waveform Recognition Based on RepNRS-LPI-Net. [PDF]

Sensors (Basel)
Liao T, Hu J.
europepmc   +1 more source

Tracking SARS-CoV-2 genomic variants in wastewater sequencing data with LolliPop. [PDF]

PLoS Comput Biol
Dreifuss D, Topolsky I, Icer Baykal P, Beerenwinkel N.   +3 more
europepmc   +1 more source

DMG-GCN: A Dynamic Microstate-Guided Graph Convolutional Network for EEG Cognitive Workload Decoding in Air Traffic Control. [PDF]

Biosensors (Basel)
Zhang Y, Shao Q, Yang H, Ren X, Peng X.
europepmc   +1 more source

Effect of database, pre-processing pipeline, and scan duration on rs-fMRI functional connectivity based treatment targets for TMS obtained using the Stanford Neuromodulation Therapy (SNT) protocol. [PDF]

Psychoradiology
Yu L, Li X, Roberts N, Huang X, Xing H.
europepmc   +1 more source

Kernel Smoothing

, 1994
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. The basic principle is that local averaging or smoothing is performed with respect to a kernel function.
Matt P. Wand, M. Chris Jones
core   +7 more sources

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Kernel covariance series smoothing

2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015
In this paper, we provide a new viewpoint of sequential random processes of the kind F(x), where x is a multivariate vector of covariates, in terms of a smoothing operation governed by a covariance function. By exploiting the eigenvalues and eigenvectors of the covariance function, we represent the smooth function in terms of an orthogonal series over ...
Cristina Soguero-Ruíz, Robert Jenssen
openaire   +1 more source

Smoothed Bagging with Kernel Bandwidth Selectors

Neural Processing Letters, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shinjae Lee, Sungzoon Cho
openaire   +3 more sources

On the Smoothness of General Kernels

Canadian Journal of Mathematics, 1966
In (3, §2), the writer and F. E. Browder stated briefly, without proof, some results concerning general distribution kernels. It is our aim here to prove and complete those results.The terminology and notations are introduced in §1.In §2 we define the notion of domain of dependence with respect to the kernel Kx,y (Definition 1) as well as the notion of
openaire   +2 more sources