Results 41 to 50 of about 411,514 (294)

Image restoration model for microscopic defocused images based on blurring kernel guidance

Heliyon
Defocus blurring imaging seriously affects the observation accuracy and application range of optical microscopes, and the blurring kernel function is a key parameter for high-resolution image restoration.
Yangjie Wei, Qifei Li, Weihan Hou
doaj   +1 more source

A Doubly Smoothed PD Estimator in Credit Risk

Proceedings, 2020
In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD estimators are proved and their behaviour is ...
Rebeca Peláez Suárez, Ricardo Cao Abad, Juan M. Vilar Fernández   +2 more
doaj   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Unsupervised Blur Kernel Estimation and Correction for Blind Super-Resolution

IEEE Access, 2022
Blind super-resolution (blind-SR) is an important task in the field of computer vision and has various applications in real-world. Blur kernel estimation is the main element of blind-SR along with the adaptive SR networks and a more accurately estimated ...
Youngsoo Kim, Jeonghyo Ha, Yooshin Cho, Junmo Kim   +3 more
doaj   +1 more source

A Kernel-Based Calculation of Information on a Metric Space

, 2013
Kernel density estimation is a technique for approximating probability distributions. Here, it is applied to the calculation of mutual information on a metric space.
Houghton, Conor J., Tobin, R. Joshua
core   +2 more sources

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

On almost sure convergence rates for the kernel estimator of a covariance operator under negative association [PDF]

Journal of Mahani Mathematical Research
It is suppose that $\{X_n,~n\geq 1\}$ is a strictly stationary sequence of negatively associated random variables with continuous distribution function F.
Hadi Jabbari
doaj   +1 more source

Serum Uric Acid Levels in Older Adults: Associations With Clinical Outcomes and Implications for Reference Intervals in Those Aged 70 Years and Over

Arthritis Care &Research, EarlyView.
Objective Reports have linked both high and low serum uric acid (SUA) levels to adverse health outcomes. This study aimed to establish a reference interval for SUA in older adults and assessed its association with clinically relevant outcomes in relatively healthy, community‐dwelling individuals aged ≥70 years old.
Amanda J. Rickard, Cammie Tran, Hans G. Schneider, Flavia M. Cicuttini, Anita E. Wluka, Ego Seeman, Johannes T. Neumann, Md Nazmul Karim, Zhen Zhou, Sultana Monira Hussain, David P. Q. Clark, Daniel Clayton‐Chubb, Andrew M. Tonkin, Lawrence J. Beilin, Robyn L. Woods, John J. McNeil   +15 more
wiley   +1 more source

Functional kernel estimators of conditional extreme quantiles [PDF]

, 2011
We address the estimation of "extreme" conditional quantiles i.e. when their order converges to one as the sample size increases. Conditions on the rate of convergence of their order to one are provided to obtain asymptotically Gaussian distributed ...
A Berlinet, BM Hill, F Caeiro, F Ferraty, I Gijbels, I Weissman, J. Pickands, J. Segers, JHJ Einmahl, L Gardes, L Haan de, MI Gomes, MI Gomes, T Samanta, W Stute   +14 more
core   +8 more sources

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source