Automated detection and forecasting of covid-19 using deep learning techniques: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
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 …

A review of predictive and contrastive self-supervised learning for medical images

WC Wang, E Ahn, D Feng, J Kim - Machine Intelligence Research, 2023 - Springer
Over the last decade, supervised deep learning on manually annotated big data has been
progressing significantly on computer vision tasks. But, the application of deep learning in …

Generative adversarial network based data augmentation for CNN based detection of Covid-19

R Gulakala, B Markert, M Stoffel - Scientific Reports, 2022 - nature.com
Covid-19 has been a global concern since 2019, crippling the world economy and health.
Biological diagnostic tools have since been developed to identify the virus from bodily fluids …

Weed classification from natural corn field-multi-plant images based on shallow and deep learning

F Garibaldi-Márquez, G Flores, DA Mercado-Ravell… - Sensors, 2022 - mdpi.com
Crop and weed discrimination in natural field environments is still challenging for
implementing automatic agricultural practices, such as weed control. Some weed control …

[HTML][HTML] Machine learning, deep learning, and mathematical models to analyze forecasting and epidemiology of COVID-19: a systematic literature review

F Saleem, ASAM Al-Ghamdi, MO Alassafi… - International journal of …, 2022 - mdpi.com
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide
pandemic by the World Health Organization due to its rapid spread. Since the first case was …

COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization

A Hamza, M Attique Khan, SH Wang… - Frontiers in Public …, 2022 - frontiersin.org
Coronavirus disease 2019 (COVID-19) is a highly contagious disease that has claimed the
lives of millions of people worldwide in the last 2 years. Because of the disease's rapid …

Covid-19net: An effective and robust approach for covid-19 detection using ensemble of convnet-24 and customized pre-trained models

P Elangovan, D Vijayalakshmi, MK Nath - Circuits, Systems, and Signal …, 2024 - Springer
The Coronavirus is extremely harmful to human lungs, and hence early detection is critical to
prevent the virus from spreading. However, the cumulative workflow in the routine diagnostic …

A CNN‐Based Chest Infection Diagnostic Model: A Multistage Multiclass Isolated and Developed Transfer Learning Framework

MU Ali, KD Kallu, H Masood, U Tahir… - … Journal of Intelligent …, 2023 - Wiley Online Library
In 2019, a deadly coronaviral infection (COVID‐19) that infected millions of people globally
was detected in China. This fatal virus affects the respiratory system and currently spreads to …

Contribution to pulmonary diseases diagnostic from X-ray images using innovative deep learning models

A Bennour, NB Aoun, OI Khalaf, F Ghabban, WK Wong… - Heliyon, 2024 - cell.com
Pulmonary disease identification and characterization are among the most intriguing
research topics of recent years since they require an accurate and prompt diagnosis …

Employing Transfer Learning for Diagnosing COVID-19 Disease.

LR Ali, SA Jebur, MM Jahefer… - International Journal of …, 2022 - search.ebscohost.com
Corona virus's correct and accurate diagnosis is the most important reason for contributing
to the treatment of this disease. Radiography is one of the simplest methods to detect virus …