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Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review
The goal of managing smart cities and societies is to maximize the efficient use of finite
resources while enhancing the quality of life. To establish a sustainable urban existence …
resources while enhancing the quality of life. To establish a sustainable urban existence …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Machine learning applications for COVID-19 outbreak management
Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …
practically every area of human life. Several machine learning (ML) approaches are …
[HTML][HTML] Paradigm shift from Artificial Neural Networks (ANNs) to deep Convolutional Neural Networks (DCNNs) in the field of medical image processing
Images and other types of unstructural data in the medical domain are rapidly becoming
data-intensive. Actionable insights from these complex data present new opportunities but …
data-intensive. Actionable insights from these complex data present new opportunities but …
[HTML][HTML] A comprehensive review of machine learning used to combat COVID-19
Coronavirus disease (COVID-19) has had a significant impact on global health since the
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …
start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed …
Forward layer-wise learning of convolutional neural networks through separation index maximizing
A Karimi, A Kalhor, M Sadeghi Tabrizi - Scientific Reports, 2024 - nature.com
This paper proposes a forward layer-wise learning algorithm for CNNs in classification
problems. The algorithm utilizes the Separation Index (SI) as a supervised complexity …
problems. The algorithm utilizes the Separation Index (SI) as a supervised complexity …
[HTML][HTML] A systematic review on deep structured learning for COVID-19 screening using chest CT from 2020 to 2022
The emergence of the COVID-19 pandemic in Wuhan in 2019 led to the discovery of a novel
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
coronavirus. The World Health Organization (WHO) designated it as a global pandemic on …
[HTML][HTML] Swin-textural: A novel textural features-based image classification model for COVID-19 detection on chest computed tomography
Background Chest computed tomography (CT) has a high sensitivity for detecting COVID-19
lung involvement and is widely used for diagnosis and disease monitoring. We proposed a …
lung involvement and is widely used for diagnosis and disease monitoring. We proposed a …
[HTML][HTML] Evae-net: An ensemble variational autoencoder deep learning network for covid-19 classification based on chest x-ray images
The COVID-19 pandemic has had a significant impact on many lives and the economies of
many countries since late December 2019. Early detection with high accuracy is essential to …
many countries since late December 2019. Early detection with high accuracy is essential to …
Unraveling complex relationships between COVID-19 risk factors using machine learning based models for predicting mortality of hospitalized patients and …
Background At the end of 2019, the coronavirus disease 2019 (COVID-19) pandemic
increased the hospital burden of COVID-19 caused by the SARS-Cov-2 and became the …
increased the hospital burden of COVID-19 caused by the SARS-Cov-2 and became the …