AIMC Topic: Neural Networks, Computer

Clear Filters Showing 15621 to 15630 of 31376 articles

Detection of Fake News Text Classification on COVID-19 Using Deep Learning Approaches.

Computational and mathematical methods in medicine
A vast amount of data is generated every second for microblogs, content sharing via social media sites, and social networking. Twitter is an essential popular microblog where people voice their opinions about daily issues. Recently, analyzing these o...

An Optimized Hybrid Deep Learning Model to Detect COVID-19 Misleading Information.

Computational intelligence and neuroscience
Fake news is challenging to detect due to mixing accurate and inaccurate information from reliable and unreliable sources. Social media is a data source that is not trustworthy all the time, especially in the COVID-19 outbreak. During the COVID-19 ep...

How to predict relapse in leukemia using time series data: A comparative in silico study.

PloS one
Risk stratification and treatment decisions for leukemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, there is increasing evidence that linking quantitat...

Automatic Multi-Label ECG Classification with Category Imbalance and Cost-Sensitive Thresholding.

Biosensors
Automatic electrocardiogram (ECG) classification is a promising technology for the early screening and follow-up management of cardiovascular diseases. It is, by nature, a multi-label classification task owing to the coexistence of different kinds of...

Rapid identification of ore minerals using multi-scale dilated convolutional attention network associated with portable Raman spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Electron portable Raman spectroscopy tools for ore mineral identification are widely used in raw ore analysis and mineral process engineering. This paper demonstrates an extremely fast and accurate method for identifying unknown ore mineral samples b...

Understanding and mitigating noise in trained deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks unlocked a vast range of new applications by solving tasks of which many were previously deemed as reserved to higher human intelligence. One of the developments enabling this success was a boost in computing power provided by sp...

Stability and dissipativity criteria for neural networks with time-varying delays via an augmented zero equality approach.

Neural networks : the official journal of the International Neural Network Society
This work investigates the stability and dissipativity problems for neural networks with time-varying delay. By the construction of new augmented Lyapunov-Krasovskii functionals based on integral inequality and the use of zero equality approach, thre...

Generative Adversarial Networks in Cardiology.

The Canadian journal of cardiology
Generative adversarial networks (GANs) are state-of-the-art neural network models used to synthesise images and other data. GANs brought a considerable improvement to the quality of synthetic data, quickly becoming the standard for data-generation ta...

Amino acid environment affinity model based on graph attention network.

Journal of bioinformatics and computational biology
Proteins are engines involved in almost all functions of life. They have specific spatial structures formed by twisting and folding of one or more polypeptide chains composed of amino acids. Protein sites are protein structure microenvironments that ...

A Continuous Learning Approach for Real-Time Network Intrusion Detection.

International journal of neural systems
Network intrusion detection is becoming a challenging task with cyberattacks that are becoming more and more sophisticated. Failing the prevention or detection of such intrusions might have serious consequences. Machine learning approaches try to rec...