Medical & biological engineering & computing
Dec 14, 2018
Skeletal muscle forces may be estimated using rigid musculoskeletal models and neural networks. Neural network (NN) approach has the advantages of real-time estimation ability and promising prediction accuracy. However, most of the developed NN model...
Neural networks : the official journal of the International Neural Network Society
Dec 14, 2018
Complex networks provide a powerful tool for data representation due to its ability to describe the interplay between topological, functional, and dynamical properties of the input data. A fundamental process in network-based (graph-based) data analy...
Neural networks : the official journal of the International Neural Network Society
Dec 14, 2018
Despite the superior performance of deep learning in many applications, challenges remain in the area of regression on function spaces. In particular, neural networks are unable to encode function inputs compactly as each node encodes just a real val...
OBJECTIVES: Neural networks are a powerful statistical tool that use nonlinear regression type models to obtain predictions. Their use in the Lifeways cross-generation study that examined body mass index (BMI) of children, among other measures, is ex...
IEEE transactions on neural networks and learning systems
Dec 12, 2018
Neural decoding, which aims to predict external visual stimuli information from evoked brain activities, plays an important role in understanding human visual system. Many existing methods are based on linear models, and most of them only focus on ei...
Environmental pollution (Barking, Essex : 1987)
Dec 12, 2018
Heavy metals and emerging engineered nanoparticles (ENPs) are two current environmental concerns that have attracted considerable attention. Cerium oxide nanoparticles (CeONPs) are now used in a plethora of industrial products, while cadmium (Cd) is ...
Neural networks : the official journal of the International Neural Network Society
Dec 12, 2018
This paper considers the global asymptotical synchronization of fractional-order memristive complex-valued neural networks (FOMCVNN), with both parameter uncertainties and multiple time delays. Sufficient conditions of uncertain FOMCVNN, with multipl...
AJR. American journal of roentgenology
Dec 12, 2018
OBJECTIVE: The purpose of this study is to determine whether a convolutional neural network (CNN) can predict the maximum standardized uptake value (SUV) of lymph nodes in patients with cancer using the unenhanced CT images from a PET/CT examination,...
BACKGROUND: A fully convolutional neural networks (FCN)-based automated image analysis algorithm to discriminate between head and neck cancer and noncancerous epithelium based on nonlinear microscopic images was developed.
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