State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components pha...
RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction.
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
BACKGROUND: As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depressio...
Neural networks : the official journal of the International Neural Network Society
Jul 4, 2019
The Gaussian process (GP) is a nonparametric prior distribution over functions indexed by time, space, or other high-dimensional index set. The GP is a flexible model yet its limitation is given by its very nature: it can only model Gaussian marginal...
Medical & biological engineering & computing
Jul 4, 2019
Differentiation of real interactions between different brain regions from spurious ones has been a challenge in neuroimaging researches. While using electroencephalographic data, those spurious interactions are mostly caused by the volume conduction ...
International journal of injury control and safety promotion
Jul 4, 2019
Urban intersections in India constitute a significant share of pedestrian fatalities. However, model-based prediction of pedestrian fatalities is still in a nascent stage in India. This study proposes an artificial neural network (ANN) technique to d...
Stomata regulate important physiological processes in plants and are often phenotyped by researchers in diverse fields of plant biology. Currently, there are no user-friendly, fully automated methods to perform the task of identifying and counting st...
Combining machine learning with neuroimaging data has a great potential for early diagnosis of mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, it remains unclear how well the classifiers built on one population can predict MCI/...
Computational intelligence and neuroscience
Jul 4, 2019
In today's society, image resources are everywhere, and the number of available images can be overwhelming. Determining how to rapidly and effectively query, retrieve, and organize image information has become a popular research topic, and automatic ...
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