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SEM-Net: Deep features selections with Binary Particle Swarm Optimization Method for classification of scanning electron microscope images
(Elsevier, 2021)
Materials Science is increasingly handling artificial intelligence methods to address the complexity in the field of everyday life necessities. Researchers in both academia and industry are interested in imaging techniques ...
MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
(Elsevier, 2022)
COVID-19PneumoniaArtificial intelligence (AI)Deep learningComputed tomography (CT)
MTU-COVNet: A hybrid methodology for diagnosing the COVID-19 pneumonia with optimized features from multi-net
(elsevier, 2022)
Purpose
The aim of this study was to establish and evaluate a fully automatic deep learning system for the diagnosis of COVID-19 using thoracic computed tomography (CT).
Materials and methods
In this retrospective study, ...
When machine learning meets fractional-order chaotic signals: detecting dynamical variations
(Elsevier, 2022)
The challenge of classifying multivariate time series generated by discrete and continuous dynamical systems according to their chaotic or non-chaotic behavior has been studied extensively in the literature. The examination ...