AIMC Topic: Neural Networks, Computer

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Graph Signal Processing, Graph Neural Network and Graph Learning on Biological Data: A Systematic Review.

IEEE reviews in biomedical engineering
Graph networks can model data observed across different levels of biological systems that span from population graphs (with patients as network nodes) to molecular graphs that involve omics data. Graph-based approaches have shed light on decoding bio...

TopicBERT: A Topic-Enhanced Neural Language Model Fine-Tuned for Sentiment Classification.

IEEE transactions on neural networks and learning systems
Sentiment classification is a form of data analytics where people's feelings and attitudes toward a topic are mined from data. This tantalizing power to "predict the zeitgeist" means that sentiment classification has long attracted interest, but with...

Deep learning in random neural fields: Numerical experiments via neural tangent kernel.

Neural networks : the official journal of the International Neural Network Society
A biological neural network in the cortex forms a neural field. Neurons in the field have their own receptive fields, and connection weights between two neurons are random but highly correlated when they are in close proximity in receptive fields. In...

Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes.

Environmental science and pollution research international
Sediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer pipe hydraulic capacity and transport of pollution are the main consequences of continuous sedimentation. Among different design approaches, the non-...

Negation-based transfer learning for improving biomedical Named Entity Recognition and Relation Extraction.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVES: Named Entity Recognition (NER) and Relation Extraction (RE) are two of the most studied tasks in biomedical Natural Language Processing (NLP). The detection of specific terms and entities and the relationships between them ...

Machine learning concepts applied to oral pathology and oral medicine: A convolutional neural networks' approach.

Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
INTRODUCTION: Artificial intelligence models and networks can learn and process dense information in a short time, leading to an efficient, objective, and accurate clinical and histopathological analysis, which can be useful to improve treatment moda...

Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Analytical chemistry
Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefo...

Infrared and Visible Image Fusion Technology and Application: A Review.

Sensors (Basel, Switzerland)
The images acquired by a single visible light sensor are very susceptible to light conditions, weather changes, and other factors, while the images acquired by a single infrared light sensor generally have poor resolution, low contrast, low signal-to...

A Synthetic Data Generation Technique for Enhancement of Prediction Accuracy of Electric Vehicles Demand.

Sensors (Basel, Switzerland)
In terms of electric vehicles (EVs), electric kickboards are crucial elements of smart transportation networks for short-distance travel that is risk-free, economical, and environmentally friendly. Forecasting the daily demand can improve the local s...

Classification of Acoustic Influences Registered with Phase-Sensitive OTDR Using Pattern Recognition Methods.

Sensors (Basel, Switzerland)
This article is devoted to the development of a classification method based on an artificial neural network architecture to solve the problem of recognizing the sources of acoustic influences recorded by a phase-sensitive OTDR. At the initial stage o...