Results 71 to 80 of about 196,185 (268)

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

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

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe, Keizo Sugaya, Kentaro Hayashi, Keiko Hino, Yasuhiro Nakata, Kota Bokuda, Toshio Shimizu, Kazushi Takahashi   +7 more
wiley   +1 more source

Leveraging Gaussian Processes in Remote Sensing

Energies
Power grid reliability is crucial to supporting critical infrastructure, but monitoring and maintenance activities are expensive and sometimes dangerous.
Emma Foley
doaj   +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

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias, Federica Avantaggiato, Gianni Pezzoli, Andrea Canessa   +3 more
wiley   +1 more source

Sparse Simulation of Autoregressive Gaussian Processes

Mathematics
This study proposes a novel and improved numerical approximation of the simulation of Gaussian process autoregressive models. As a Bayesian nonparametric regression method, Gaussian process models offer the unique advantage of providing closed-form ...
Tadej Krivec, Juš Kocijan
doaj   +1 more source

The Use of Genetic Algorithms for Searching Parameter Space in Gaussian Process Modeling

Journal of Telecommunications and Information Technology, 2015
The aim of the paper is to present the possibilities of modeling the experimental data by Gaussian processes. Genetic algorithms are used for finding the Gaussian process parameters.
Agnieszka Krok
doaj   +1 more source

Gaussian process dynamic programming [PDF]

Neurocomputing, 2009
Reinforcement learning (RL) and optimal control of systems with continuous states and actions require approximation techniques in most interesting cases. In this article, we introduce Gaussian process dynamic programming (GPDP), an approximate value function-based RL algorithm.
Marc Peter Deisenroth, Carl Edward Rasmussen, Jan Peters 0001   +2 more
openaire   +3 more sources