Results 51 to 60 of about 844,595 (275)

Distributed Gaussian Processes With Uncertain Inputs

IEEE Access
Gaussian Process regression is a powerful non-parametric approach that facilitates probabilistic uncertainty quantification in machine learning. Distributed Gaussian Process (DGP) methods offer scalable solutions by dividing data among multiple GP models
Peter L. Green
doaj   +1 more source

A comparison of geometric- and regression-based mobile gaze-tracking

Frontiers in Human Neuroscience, 2014
Video-based gaze-tracking systems are typically restricted in terms of their effective tracking space. This constraint limits the use of eyetrackers in studying mobile human behavior.
Björn eBrowatzki, Heinrich H. Bülthoff, Heinrich H. Bülthoff, Lewis L. Chuang   +3 more
doaj   +1 more source

Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques

Sensors, 2020
Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality of ...
Gurjinder S. Baath, Harpinder K. Baath, Prasanna H. Gowda, Johnson P. Thomas, Brian K. Northup, Srinivas C. Rao, Hardeep Singh   +6 more
doaj   +1 more source

The MMP‐9/TIMP‐1 Ratio and Concentrations of Osteopontin Are Elevated in Cerebrospinal Fluid of People With Multiple Sclerosis and Decrease After Autologous Hematopoietic Stem Cell Transplantation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives To evaluate the utility of cerebrospinal fluid (CSF) biomarkers—matrix metalloproteinase‐9 (MMP‐9), tissue inhibitor of metalloproteinases‐1 (TIMP‐1), the MMP‐9/TIMP‐1 ratio, and osteopontin (OPN)—as indicators of blood–brain barrier (BBB) integrity and disease activity in people with relapsing–remitting multiple sclerosis (pwMS ...
Ivan Pavlovic, Ida Erngren, Kim Kultima, Anders Larsson, Malin Müller, Anna Wiberg, Joachim Burman   +6 more
wiley   +1 more source

Distributed Multi-Robot Information Gathering under Spatio-Temporal Inter-Robot Constraints

Sensors, 2020
Information gathering (IG) algorithms aim to intelligently select the mobile robotic sensor actions required to efficiently obtain an accurate reconstruction of a physical process, such as an occupancy map, a wind field, or a magnetic field.
Alberto Viseras, Zhe Xu, Luis Merino
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

Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)

Remote Sensing, 2018
The main objective of this research is to investigate the potential combination of Sentinel-2A and ALOS-2 PALSAR-2 (Advanced Land Observing Satellite -2 Phased Array type L-band Synthetic Aperture Radar-2) imagery for improving the accuracy of the ...
Sasan Vafaei, Javad Soosani, Kamran Adeli, Hadi Fadaei, Hamed Naghavi, Tien Dat Pham, Dieu Tien Bui   +6 more
doaj   +1 more source

Reconstructing Probability Distributions with Gaussian Processes

, 2019
Modern cosmological analyses constrain physical parameters using Markov Chain Monte Carlo (MCMC) or similar sampling techniques. Oftentimes, these techniques are computationally expensive to run and require up to thousands of CPU hours to complete.
McClintock, Thomas, Rozo, Eduardo
core   +1 more source

Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende, Emilien Petit, Young Woo Park, Sophie Tezenas du Montcel, James M. Joers, Jonathan M. DuBois, H. Moore Arnold, Michal Povazan, Ipek Özdemir, Guita Banan, Romain Valabregue, Philipp Ehses, Jennifer Faber, Chiadi U. Onyike, Peter B. Barker, Jeremy D. Schmahmann, Eva‐Maria Ratai, Sub H. Subramony, Thomas H. Mareci, Khalaf O. Bushara, Henry Paulson, Thomas Klockgether, Alexandra Durr, Tetsuo Ashizawa, Christophe Lenglet, Gülin Öz, READISCA Investigators   +26 more
wiley   +1 more source

Dynamic switching control of buck converters using unsupervised machine learning methods

The Journal of Engineering, 2020
This study presents the implementation of a new unsupervised machine learning based system called a buck converter controller using unsupervised machine learning (ABCML) to control the operation of a type of switching voltage regulators, commonly called ...
Brook W. Abegaz
doaj   +1 more source