AIMC Topic: Neural Networks, Computer

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Comparison Study on the Estimation of the Spatial Distribution of Regional Soil Metal(loid)s Pollution Based on Kriging Interpolation and BP Neural Network.

International journal of environmental research and public health
Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this stu...

Modeling and Multiresponse Optimization for Anaerobic Codigestion of Oil Refinery Wastewater and Chicken Manure by Using Artificial Neural Network and the Taguchi Method.

BioMed research international
To study the optimum process conditions for pretreatments and anaerobic codigestion of oil refinery wastewater (ORWW) with chicken manure, L (3) Taguchi's orthogonal array was applied. The biogas production (BGP), biomethane content (BMP), and chemic...

Focal Onset Seizure Prediction Using Convolutional Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper investigates the hypothesis that focal seizures can be predicted using scalp electroencephalogram (EEG) data. Our first aim is to learn features that distinguish between the interictal and preictal regions. The second aim is to ...

[Advantages and Application Prospects of Deep Learning in Image Recognition and Bone Age Assessment].

Fa yi xue za zhi
Deep learning and neural network models have been new research directions and hot issues in the fields of machine learning and artificial intelligence in recent years. Deep learning has made a breakthrough in the applications of image and speech reco...

Metric learning with spectral graph convolutions on brain connectivity networks.

NeuroImage
Graph representations are often used to model structured data at an individual or population level and have numerous applications in pattern recognition problems. In the field of neuroscience, where such representations are commonly used to model str...

STDP-based spiking deep convolutional neural networks for object recognition.

Neural networks : the official journal of the International Neural Network Society
Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively sha...

Automatic mining of symptom severity from psychiatric evaluation notes.

International journal of methods in psychiatric research
OBJECTIVES: As electronic mental health records become more widely available, several approaches have been suggested to automatically extract information from free-text narrative aiming to support epidemiological research and clinical decision-making...

Identification of significant factors in fatal-injury highway crashes using genetic algorithm and neural network.

Accident; analysis and prevention
Identification of the significant factors of traffic crashes has been a primary concern of the transportation safety research community for many years. A fatal-injury crash is a comprehensive result influenced by multiple variables involved at the mo...

OnARTMAP: A Fuzzy ARTMAP-based Architecture.

Neural networks : the official journal of the International Neural Network Society
Fuzzy ARTMAP (FAM) copes with the stability-plasticity dilemma by the adaptive resonance theory (ART). Despite such an advantage, Fuzzy ARTMAP suffers from a category proliferation problem, which leads to a high number of categories and a decrease in...

A deep learning method for classifying mammographic breast density categories.

Medical physics
PURPOSE: Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density...