Computational intelligence and neuroscience
Apr 1, 2019
Accurate prediction of the short time series with highly irregular behavior is a challenging task found in many areas of modern science. Such data fluctuations are not systematic and hardly predictable. In recent years, artificial neural networks hav...
We introduce Bayesian QuickNAT for the automated quality control of whole-brain segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we also present inherent measures of segmentation uncertainty that allow for qualit...
International journal of computer assisted radiology and surgery
Mar 22, 2019
PURPOSE: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to address the inverse problem of converting pixel-wise multispectral reflectan...
Computational intelligence and neuroscience
Mar 12, 2019
Equipment parallel simulation is an emerging simulation technology in recent years, and equipment remaining useful life (RUL) prediction oriented parallel simulation is an important branch of parallel simulation. An important concept in equipment par...
Computational intelligence and neuroscience
Mar 3, 2019
At present, research on hesitant fuzzy operations and measures is based on equal length processing, and an equal length processing method will inevitably destroy the original data structure and change the data information. This is an urgent problem t...
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...
Neural networks : the official journal of the International Neural Network Society
Feb 7, 2019
This paper considers the finite-time cluster synchronization (FTCS) of coupled fuzzy cellular neural networks (FCNNs) with Markovian switching topology, discontinuous activation functions, proportional leakage, and time-varying unbounded delays. Nove...
Neural networks : the official journal of the International Neural Network Society
Jan 29, 2019
This paper investigates the synchronization issue for a family of time-delayed fractional-order complex dynamical networks (FCDNs) with time delay, unknown bounded uncertainty and disturbance. A novel fractional uncertainty and disturbance estimator ...
IEEE transactions on neural networks and learning systems
Dec 25, 2018
This paper presents a complex network model consisting of N uncertain reaction-diffusion neural networks with multiple time delays. We analyze the passivity and synchronization of the proposed network model and derive several passivity and synchroniz...
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Dec 19, 2018
In this work, an uncertainty optimization approach for dental implant is proposed to reduce the stress at implant-bone interface. Finite element method is utilized to calculate the stress at implant-bone interface, and support vector regression is us...