AIMC Topic: Neural Networks, Computer

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Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.

IEEE transactions on medical imaging
In this paper, we propose a generalization of the level set segmentation approach by supplying a novel method for adaptive estimation of active contour parameters. The presented segmentation method is fully automatic once the lesion has been detected...

An Improved Ensemble of Random Vector Functional Link Networks Based on Particle Swarm Optimization with Double Optimization Strategy.

PloS one
For ensemble learning, how to select and combine the candidate classifiers are two key issues which influence the performance of the ensemble system dramatically. Random vector functional link networks (RVFL) without direct input-to-output links is o...

Aerodynamic parameters from distributed heterogeneous CNT hair sensors with a feedforward neural network.

Bioinspiration & biomimetics
Distributed arrays of artificial hair sensors have bio-like sensing capabilities to obtain spatial and temporal surface flow information which is an important aspect of an effective fly-by-feel system. The spatiotemporal surface flow measurement enab...

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality.

PloS one
Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a ...

Dissipativity and stability analysis of fractional-order complex-valued neural networks with time delay.

Neural networks : the official journal of the International Neural Network Society
As we know, the notion of dissipativity is an important dynamical property of neural networks. Thus, the analysis of dissipativity of neural networks with time delay is becoming more and more important in the research field. In this paper, the author...

Improved exponential convergence result for generalized neural networks including interval time-varying delayed signals.

Neural networks : the official journal of the International Neural Network Society
This article examines the exponential stability analysis problem of generalized neural networks (GNNs) including interval time-varying delayed states. A new improved exponential stability criterion is presented by establishing a proper Lyapunov-Kraso...

DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks.

IEEE transactions on medical imaging
In this paper, we propose DeepCut, a method to obtain pixelwise object segmentations given an image dataset labelled weak annotations, in our case bounding boxes. It extends the approach of the well-known GrabCut [1] method to include machine learnin...

Application of radial basis function neural network to predict soil sorption partition coefficient using topological descriptors.

Chemosphere
The soil sorption partition coefficient logK is an indispensable parameter that can be used in assessing the environmental risk of organic chemicals. In order to predict soil sorption partition coefficient for different and even unknown compounds in ...

Predicting the Fine Particle Fraction of Dry Powder Inhalers Using Artificial Neural Networks.

Journal of pharmaceutical sciences
Dry powder inhalers are increasingly popular for delivering drugs to the lungs for the treatment of respiratory diseases, but are complex products with multivariate performance determinants. Heuristic product development guided by in vitro aerosol pe...

Robust learning in SpikeProp.

Neural networks : the official journal of the International Neural Network Society
Training a Spiking Neural Network using SpikeProp and its derivatives faces stability issues. Surges, marked by a sudden rise in learning cost, are a common occurrence during the learning process. They disrupt the learning process and often destabili...