AIMC Topic: Neural Networks, Computer

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Aperiodic sampled-data control for local stabilization of memristive neural networks subject to actuator saturation: Discrete-time Lyapunov approach.

ISA transactions
In this paper, the local stabilization of memristive neural networks (MNNs) with actuator saturation is investigated via aperiodic sampled-data control. Inspired by the characteristic of the control scheme, a novel sampling-interval-dependent Lyapuno...

Validation of a Whole Heart Segmentation from Computed Tomography Imaging Using a Deep-Learning Approach.

Journal of cardiovascular translational research
The aim of this study is to develop an automated deep-learning-based whole heart segmentation of ECG-gated computed tomography data. After 21 exclusions, CT acquired before transcatheter aortic valve implantation in 71 patients were reviewed and rand...

Deep learning-based parameter estimation in fetal diffusion-weighted MRI.

NeuroImage
Diffusion-weighted magnetic resonance imaging (DW-MRI) of fetal brain is challenged by frequent fetal motion and signal to noise ratio that is much lower than non-fetal imaging. As a result, accurate and robust parameter estimation in fetal DW-MRI re...

Leveraging Transfer Learning and Chemical Principles toward Interpretable Materials Properties.

Journal of chemical information and modeling
Machine learning is emerging as a new paradigm to rationalize chemical properties for deepening our understanding of chemistry and providing instructive clues on better materials performance. While the complex architecture of machine learning contrib...

Impedance Spectroscopy Dynamics of Biological Neural Elements: From Memristors to Neurons and Synapses.

The journal of physical chemistry. B
Understanding the operation of neurons and synapses is essential to reproducing biological computation. Building artificial neuromorphic networks opens the door to a new generation of faster and low-energy-consuming electronic circuits for computatio...

Image Generation for 2D-CNN Using Time-Series Signal Features from Foot Gesture Applied to Select Cobot Operating Mode.

Sensors (Basel, Switzerland)
Advances in robotics are part of reducing the burden associated with manufacturing tasks in workers. For example, the cobot could be used as a "third-arm" during the assembling task. Thus, the necessity of designing new intuitive control modalities a...

Predicting postoperative pain following root canal treatment by using artificial neural network evaluation.

Scientific reports
This study aimed to evaluate the accuracy of back propagation (BP) artificial neural network model for predicting postoperative pain following root canal treatment (RCT). The BP neural network model was developed using MATLAB 7.0 neural network toolb...

Deep Learning for Intelligent Recognition and Prediction of Endometrial Cancer.

Journal of healthcare engineering
The aim of the study was to investigate the intelligent recognition of radiomics based on the convolutional neural network (CNN) in predicting endometrial cancer (EC). In this study, 158 patients with EC in hospital were selected as the research obje...

Hybrid Improved Bird Swarm Algorithm with Extreme Learning Machine for Short-Term Power Prediction in Photovoltaic Power Generation System.

Computational intelligence and neuroscience
When a photovoltaic (PV) system is connected to the electric power grid, the power system reliability may be exposed to a threat due to its inherent randomness and volatility. Consequently, predicting PV power generation becomes necessary for reasona...

Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN).

PloS one
The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate due to risks of breast cancer. Early detection of cancer boosts increasing the survival chance up t...